Re: [agi] Seeking CYC critiques
Hi Stephen, nice to meet you. When I search the web for critiques of CYC, I can only find stuff from '90-95. If no one has written critiques of CYC since then, perhaps you could comment on how applicable those early critiques would be to the current system. For example, would CYC today at least better answer Vaughan Pratt's test questions from http://boole.stanford.edu/cyc.html? Has there been more progress toward developing a neutral source of questions to use to evaluate how performance improves with time and with implementation variations? At 01:57 AM 11/30/2008, Stephen Reed wrote: Hi Robin, There are no Cyc critiques that I know of in the last few years. I was employed seven years at Cycorp until August 2006 and my non-compete agreement expired a year later. An interesting competition was held by Project Halo in which Cycorp participated along with two other research groups to demonstrate human-level competency answering chemistry questions. Results are here. Although Cycorp performed principled deductive inference giving detailed justifications, it was judged to have performed inferior due to the complexity of its justifications and due to its long running times. The other competitors used special purpose problem solving modules whereas Cycorp used its general purpose inference engine, extended for chemistry equations as needed. My own interest is in natural language dialog systems for rapid knowledge formation. I was Cycorp's first project manager for its participation in the the DARPA Rapid Knowledge Formation project where it performed to DARPA's satisfaction, but subsequently its RKF tools never lived up to Cycorp's expectations that subject matter experts could rapidly extend the Cyc KB without Cycorp ontological engineers having to intervene. A Cycorp paper describing its KRAKEN system is here. I would be glad to answer questions about Cycorp and Cyc technology to the best of my knowledge, which is growing somewhat stale at this point. What are the best available critiques of CYC as it exists now (vs. soon after project started)? Robin Hanson [EMAIL PROTECTED] http://hanson.gmu.edu Research Associate, Future of Humanity Institute at Oxford University Associate Professor of Economics, George Mason University MSN 1D3, Carow Hall, Fairfax VA 22030- 703-993-2326 FAX: 703-993-2323 agi | Archives | Modify Your Subscription
Re: [agi] Mushed Up Decision Processes
2008/11/30 Ben Goertzel [EMAIL PROTECTED]: Could you give me a little more detail about your thoughts on this? Do you think the problem of increasing uncomputableness of complicated complexity is the common thread found in all of the interesting, useful but unscalable methods of AI? Jim Bromer Well, I think that dealing with combinatorial explosions is, in general, the great unsolved problem of AI. I think the opencog prime design can solve it, but this isn't proved yet... Good luck with that! In general, the standard AI methods can't handle pattern recognition problems requiring finding complex interdependencies among multiple variables that are obscured among scads of other variables The human mind seems to do this via building up intuition via drawing analogies among multiple problems it confronts during its history. Yes, so that people learn one problem, then it helps them to learn other similar ones. Is there any AI software that does this? I'm not aware of any. I have proposed a problem domain called function predictor whose purpose is to allow an AI to learn across problem sub-domains, carrying its learning from one domain to another. (See http://www.includipedia.com/wiki/User:Cabalamat/Function_predictor ) I also think it would be useful if there was a regular (maybe annual) competition in the function predictor domain (or some similar domain). A bit like the Loebner Prize, except that it would be more useful to the advancement of AI, since the Loebner prize is silly. -- Philip Hunt, [EMAIL PROTECTED] Please avoid sending me Word or PowerPoint attachments. See http://www.gnu.org/philosophy/no-word-attachments.html --- agi Archives: https://www.listbox.com/member/archive/303/=now RSS Feed: https://www.listbox.com/member/archive/rss/303/ Modify Your Subscription: https://www.listbox.com/member/?member_id=8660244id_secret=120640061-aded06 Powered by Listbox: http://www.listbox.com
Re: [agi] Mushed Up Decision Processes
Hi, I have proposed a problem domain called function predictor whose purpose is to allow an AI to learn across problem sub-domains, carrying its learning from one domain to another. (See http://www.includipedia.com/wiki/User:Cabalamat/Function_predictor ) I also think it would be useful if there was a regular (maybe annual) competition in the function predictor domain (or some similar domain). A bit like the Loebner Prize, except that it would be more useful to the advancement of AI, since the Loebner prize is silly. -- Philip Hunt, [EMAIL PROTECTED] How does that differ from what is generally called transfer learning ? ben g --- agi Archives: https://www.listbox.com/member/archive/303/=now RSS Feed: https://www.listbox.com/member/archive/rss/303/ Modify Your Subscription: https://www.listbox.com/member/?member_id=8660244id_secret=120640061-aded06 Powered by Listbox: http://www.listbox.com
[agi] Re: Glocal memory
A little more poking around reveals further evidence that supports the glocal model of brain memory (they talk about a distributed plus hub model, which is part of the glocality idea, though missing the nonlinear-attractor aspect that I think is critical to distributed memory) http://brain.guides.britannica.com/what-happens-when-things-go-wrong/on-the-cutting-edge-of-brain-research/on-the-cutting-edge-of-brain-research/82/3/ The paper is at http://www.nature.com/nrn/journal/v8/n12/full/nrn2277.html and some mildly critical commentary at http://talkingbrains.blogspot.com/2008/01/semantics-and-brain-more-on-atl-as-hub.html As Richard L would likely point out, the authors' data supports plenty of different interpretations, and the one presented is only one of the many plausible ones... -- ben G On Tue, Nov 25, 2008 at 12:45 AM, Ben Goertzel [EMAIL PROTECTED] wrote: A semi-technical essay on the global/local (aka glocal) nature of memory is linked to from here http://multiverseaccordingtoben.blogspot.com/ I wrote this a long while ago but just got around to posting it now... ben -- Ben Goertzel, PhD CEO, Novamente LLC and Biomind LLC Director of Research, SIAI [EMAIL PROTECTED] The empires of the future are the empires of the mind. -- Sir Winston Churchill -- Ben Goertzel, PhD CEO, Novamente LLC and Biomind LLC Director of Research, SIAI [EMAIL PROTECTED] I intend to live forever, or die trying. -- Groucho Marx --- agi Archives: https://www.listbox.com/member/archive/303/=now RSS Feed: https://www.listbox.com/member/archive/rss/303/ Modify Your Subscription: https://www.listbox.com/member/?member_id=8660244id_secret=120640061-aded06 Powered by Listbox: http://www.listbox.com
[agi] AIXI (was: Mushed Up Decision Processes)
2008/11/29 Matt Mahoney [EMAIL PROTECTED]: The general problem of detecting overfitting is not computable. The principle according to Occam's Razor, formalized and proven by Hutter's AIXI model, is to choose the shortest program (simplest hypothesis) that generates the data. Overfitting is the case of choosing a program that is too large. Can someone explain AIXI to me? My understanding is that you've got some black-box process emitting output, and you generate all possible programs that emit the same output, then choose the shortest one. You then run this program and its subsequent output is what you predict the black-box process will do. This has the minor drawback, of course, that it requires infinite processing power and is therefore slightly impractical. I've read Hutter's paper Universal algorithmic intelligence, A mathematical top-down approach which amusingly describes itself as a gentle introduction to the AIXI model. Hutter also describes AIXItl of computation time Ord(t*2^L) where I assume L is the length of the program and I'm not sure what t is. Is AIXItl something that could be practically written or is it purely a theoretical construct? In short, is there something to AIXI or is it something I can safely ignore? -- Philip Hunt, [EMAIL PROTECTED] Please avoid sending me Word or PowerPoint attachments. See http://www.gnu.org/philosophy/no-word-attachments.html --- agi Archives: https://www.listbox.com/member/archive/303/=now RSS Feed: https://www.listbox.com/member/archive/rss/303/ Modify Your Subscription: https://www.listbox.com/member/?member_id=8660244id_secret=120640061-aded06 Powered by Listbox: http://www.listbox.com
Re: [agi] AIXI (was: Mushed Up Decision Processes)
AIXI is a purely theoretic construct, requiring infinite computational resources AIXItl is a version that could be implemented in principle, but not in practice due to truly insane computational resource requirements Whether the line of thinking and body of theory underlying these things can be useful for inspiring more practical AGI designs, is a matter of opinion and intuition, at this point... -- Ben G On Sun, Nov 30, 2008 at 10:58 AM, Philip Hunt [EMAIL PROTECTED] wrote: 2008/11/29 Matt Mahoney [EMAIL PROTECTED]: The general problem of detecting overfitting is not computable. The principle according to Occam's Razor, formalized and proven by Hutter's AIXI model, is to choose the shortest program (simplest hypothesis) that generates the data. Overfitting is the case of choosing a program that is too large. Can someone explain AIXI to me? My understanding is that you've got some black-box process emitting output, and you generate all possible programs that emit the same output, then choose the shortest one. You then run this program and its subsequent output is what you predict the black-box process will do. This has the minor drawback, of course, that it requires infinite processing power and is therefore slightly impractical. I've read Hutter's paper Universal algorithmic intelligence, A mathematical top-down approach which amusingly describes itself as a gentle introduction to the AIXI model. Hutter also describes AIXItl of computation time Ord(t*2^L) where I assume L is the length of the program and I'm not sure what t is. Is AIXItl something that could be practically written or is it purely a theoretical construct? In short, is there something to AIXI or is it something I can safely ignore? -- Philip Hunt, [EMAIL PROTECTED] Please avoid sending me Word or PowerPoint attachments. See http://www.gnu.org/philosophy/no-word-attachments.html --- agi Archives: https://www.listbox.com/member/archive/303/=now RSS Feed: https://www.listbox.com/member/archive/rss/303/ Modify Your Subscription: https://www.listbox.com/member/?; Powered by Listbox: http://www.listbox.com -- Ben Goertzel, PhD CEO, Novamente LLC and Biomind LLC Director of Research, SIAI [EMAIL PROTECTED] I intend to live forever, or die trying. -- Groucho Marx --- agi Archives: https://www.listbox.com/member/archive/303/=now RSS Feed: https://www.listbox.com/member/archive/rss/303/ Modify Your Subscription: https://www.listbox.com/member/?member_id=8660244id_secret=120640061-aded06 Powered by Listbox: http://www.listbox.com
Re: [agi] Mushed Up Decision Processes
2008/11/30 Ben Goertzel [EMAIL PROTECTED]: Hi, I have proposed a problem domain called function predictor whose purpose is to allow an AI to learn across problem sub-domains, carrying its learning from one domain to another. (See http://www.includipedia.com/wiki/User:Cabalamat/Function_predictor ) I also think it would be useful if there was a regular (maybe annual) competition in the function predictor domain (or some similar domain). A bit like the Loebner Prize, except that it would be more useful to the advancement of AI, since the Loebner prize is silly. -- Philip Hunt, [EMAIL PROTECTED] How does that differ from what is generally called transfer learning ? I don't think it does differ. (Transfer learning is not a term I'd previously come across). -- Philip Hunt, [EMAIL PROTECTED] Please avoid sending me Word or PowerPoint attachments. See http://www.gnu.org/philosophy/no-word-attachments.html --- agi Archives: https://www.listbox.com/member/archive/303/=now RSS Feed: https://www.listbox.com/member/archive/rss/303/ Modify Your Subscription: https://www.listbox.com/member/?member_id=8660244id_secret=120640061-aded06 Powered by Listbox: http://www.listbox.com
Re: [agi] Seeking CYC critiques
Robin, While I was at Cycorp, a concerted effort was made to address Vaughan Pratt's test questions. I recall that most of them required the addition of facts and rules into the Cyc KB so that they would answer. I believe that a substantial portion are included in the Cyc query regression test used to maintain the KB quality. This regression test is proprietary to Cycorp, and has not been released even in ResearchCyc that I know of. Also, Cycorp has been working on using an extract of the Cyc KB as a resource for evaluating theorem provers, described here. Cheers, -Steve Stephen L. Reed Artificial Intelligence Researcher http://texai.org/blog http://texai.org 3008 Oak Crest Ave. Austin, Texas, USA 78704 512.791.7860 From: Robin Hanson [EMAIL PROTECTED] To: agi@v2.listbox.com Sent: Sunday, November 30, 2008 7:43:38 AM Subject: Re: [agi] Seeking CYC critiques Hi Stephen, nice to meet you. When I search the web for critiques of CYC, I can only find stuff from '90-95. If no one has written critiques of CYC since then, perhaps you could comment on how applicable those early critiques would be to the current system. For example, would CYC today at least better answer Vaughan Pratt's test questions from http://boole.stanford.edu/cyc.html? Has there been more progress toward developing a neutral source of questions to use to evaluate how performance improves with time and with implementation variations? At 01:57 AM 11/30/2008, Stephen Reed wrote: Hi Robin, There are no Cyc critiques that I know of in the last few years. I was employed seven years at Cycorp until August 2006 and my non-compete agreement expired a year later. An interesting competition was held by Project Halo in which Cycorp participated along with two other research groups to demonstrate human-level competency answering chemistry questions. Results are here. Although Cycorp performed principled deductive inference giving detailed justifications, it was judged to have performed inferior due to the complexity of its justifications and due to its long running times. The other competitors used special purpose problem solving modules whereas Cycorp used its general purpose inference engine, extended for chemistry equations as needed. My own interest is in natural language dialog systems for rapid knowledge formation. I was Cycorp's first project manager for its participation in the the DARPA Rapid Knowledge Formation project where it performed to DARPA's satisfaction, but subsequently its RKF tools never lived up to Cycorp's expectations that subject matter experts could rapidly extend the Cyc KB without Cycorp ontological engineers having to intervene. A Cycorp paper describing its KRAKEN system is here. I would be glad to answer questions about Cycorp and Cyc technology to the best of my knowledge, which is growing somewhat stale at this point. What are the best available critiques of CYC as it exists now (vs. soon after project started)? Robin Hanson [EMAIL PROTECTED] http://hanson.gmu.edu Research Associate, Future of Humanity Institute at Oxford University Associate Professor of Economics, George Mason University MSN 1D3, Carow Hall, Fairfax VA 22030- 703-993-2326 FAX: 703-993-2323 agi | Archives | Modify Your Subscription --- agi Archives: https://www.listbox.com/member/archive/303/=now RSS Feed: https://www.listbox.com/member/archive/rss/303/ Modify Your Subscription: https://www.listbox.com/member/?member_id=8660244id_secret=120640061-aded06 Powered by Listbox: http://www.listbox.com
Re: [agi] Mushed Up Decision Processes
Ben, Cycorp participated in the DARPA Transfer Learning project, as a subcontractor. My project role was simply a team member and I did not attend any PI meetings. But I did work on getting a Quake III Arena environment working at Cycorp which was to be a transfer learning testbed. I also enhanced Cycorp's Java application that gathered facts from the web using the Google API. Regarding winning a DARPA contract, I believe that teaming with an established contractor, e.g. SAIC, SRI, is beneficial. Cheers, -Steve Stephen L. Reed Artificial Intelligence Researcher http://texai.org/blog http://texai.org 3008 Oak Crest Ave. Austin, Texas, USA 78704 512.791.7860 From: Ben Goertzel [EMAIL PROTECTED] To: agi@v2.listbox.com Sent: Sunday, November 30, 2008 10:17:44 AM Subject: Re: [agi] Mushed Up Decision Processes There was a DARPA program on transfer learning a few years back ... I believe I applied and got rejected (with perfect marks on the technical proposal, as usual ...) ... I never checked to see who got the $$ and what they did with it... ben g On Sun, Nov 30, 2008 at 11:12 AM, Philip Hunt [EMAIL PROTECTED] wrote: 2008/11/30 Ben Goertzel [EMAIL PROTECTED]: Hi, I have proposed a problem domain called function predictor whose purpose is to allow an AI to learn across problem sub-domains, carrying its learning from one domain to another. (See http://www.includipedia.com/wiki/User:Cabalamat/Function_predictor ) I also think it would be useful if there was a regular (maybe annual) competition in the function predictor domain (or some similar domain). A bit like the Loebner Prize, except that it would be more useful to the advancement of AI, since the Loebner prize is silly. -- Philip Hunt, [EMAIL PROTECTED] How does that differ from what is generally called transfer learning ? I don't think it does differ. (Transfer learning is not a term I'd previously come across). -- Philip Hunt, [EMAIL PROTECTED] Please avoid sending me Word or PowerPoint attachments. See http://www.gnu.org/philosophy/no-word-attachments.html --- agi Archives: https://www.listbox.com/member/archive/303/=now RSS Feed: https://www.listbox.com/member/archive/rss/303/ Modify Your Subscription: https://www.listbox.com/member/?; Powered by Listbox: http://www.listbox.com -- Ben Goertzel, PhD CEO, Novamente LLC and Biomind LLC Director of Research, SIAI [EMAIL PROTECTED] I intend to live forever, or die trying. -- Groucho Marx --- agi Archives: https://www.listbox.com/member/archive/303/=now RSS Feed: https://www.listbox.com/member/archive/rss/303/ Modify Your Subscription: https://www.listbox.com/member/?; Powered by Listbox: http://www.listbox.com --- agi Archives: https://www.listbox.com/member/archive/303/=now RSS Feed: https://www.listbox.com/member/archive/rss/303/ Modify Your Subscription: https://www.listbox.com/member/?member_id=8660244id_secret=120640061-aded06 Powered by Listbox: http://www.listbox.com
Re: [agi] Mushed Up Decision Processes
Matt Taylor was also an intern at Cycorp where was on Cycorp's Transfer Learning team with me. -Steve Stephen L. Reed Artificial Intelligence Researcher http://texai.org/blog http://texai.org 3008 Oak Crest Ave. Austin, Texas, USA 78704 512.791.7860 From: Pei Wang [EMAIL PROTECTED] To: agi@v2.listbox.com Sent: Sunday, November 30, 2008 10:48:59 AM Subject: Re: [agi] Mushed Up Decision Processes On Sun, Nov 30, 2008 at 11:17 AM, Ben Goertzel [EMAIL PROTECTED] wrote: There was a DARPA program on transfer learning a few years back ... I believe I applied and got rejected (with perfect marks on the technical proposal, as usual ...) ... I never checked to see who got the $$ and what they did with it... See http://www.cs.utexas.edu/~mtaylor/Publications/AGI08-taylor.pdf Pei ben g On Sun, Nov 30, 2008 at 11:12 AM, Philip Hunt [EMAIL PROTECTED] wrote: 2008/11/30 Ben Goertzel [EMAIL PROTECTED]: Hi, I have proposed a problem domain called function predictor whose purpose is to allow an AI to learn across problem sub-domains, carrying its learning from one domain to another. (See http://www.includipedia.com/wiki/User:Cabalamat/Function_predictor ) I also think it would be useful if there was a regular (maybe annual) competition in the function predictor domain (or some similar domain). A bit like the Loebner Prize, except that it would be more useful to the advancement of AI, since the Loebner prize is silly. -- Philip Hunt, [EMAIL PROTECTED] How does that differ from what is generally called transfer learning ? I don't think it does differ. (Transfer learning is not a term I'd previously come across). -- Philip Hunt, [EMAIL PROTECTED] Please avoid sending me Word or PowerPoint attachments. See http://www.gnu.org/philosophy/no-word-attachments.html --- agi Archives: https://www.listbox.com/member/archive/303/=now RSS Feed: https://www.listbox.com/member/archive/rss/303/ Modify Your Subscription: https://www.listbox.com/member/?; Powered by Listbox: http://www.listbox.com -- Ben Goertzel, PhD CEO, Novamente LLC and Biomind LLC Director of Research, SIAI [EMAIL PROTECTED] I intend to live forever, or die trying. -- Groucho Marx --- agi Archives: https://www.listbox.com/member/archive/303/=now RSS Feed: https://www.listbox.com/member/archive/rss/303/ Modify Your Subscription: https://www.listbox.com/member/?; Powered by Listbox: http://www.listbox.com --- agi Archives: https://www.listbox.com/member/archive/303/=now RSS Feed: https://www.listbox.com/member/archive/rss/303/ Modify Your Subscription: https://www.listbox.com/member/?; Powered by Listbox: http://www.listbox.com --- agi Archives: https://www.listbox.com/member/archive/303/=now RSS Feed: https://www.listbox.com/member/archive/rss/303/ Modify Your Subscription: https://www.listbox.com/member/?member_id=8660244id_secret=120640061-aded06 Powered by Listbox: http://www.listbox.com
Re: [agi] Mushed Up Decision Processes
Regarding winning a DARPA contract, I believe that teaming with an established contractor, e.g. SAIC, SRI, is beneficial. Cheers, -Steve Yeah, I've tried that approach too ... As it happens, I've had significant more success getting funding from various other government agencies ... but DARPA has been the *least* favorable toward my work of any of them I've tried to deal with It seems that, in the 5 years I've been applying for such grants, DARPA hasn't happened to have a program manager whose particular taste in AI is compatible with mine... -- Ben G --- agi Archives: https://www.listbox.com/member/archive/303/=now RSS Feed: https://www.listbox.com/member/archive/rss/303/ Modify Your Subscription: https://www.listbox.com/member/?member_id=8660244id_secret=120640061-aded06 Powered by Listbox: http://www.listbox.com
Re: [agi] Mushed Up Decision Processes
Stephen, Does that mean what you did at Cycorp on transfer learning is similar to what Taylor presented to AGI-08? Pei On Sun, Nov 30, 2008 at 1:01 PM, Stephen Reed [EMAIL PROTECTED] wrote: Matt Taylor was also an intern at Cycorp where was on Cycorp's Transfer Learning team with me. -Steve Stephen L. Reed Artificial Intelligence Researcher http://texai.org/blog http://texai.org 3008 Oak Crest Ave. Austin, Texas, USA 78704 512.791.7860 From: Pei Wang [EMAIL PROTECTED] To: agi@v2.listbox.com Sent: Sunday, November 30, 2008 10:48:59 AM Subject: Re: [agi] Mushed Up Decision Processes On Sun, Nov 30, 2008 at 11:17 AM, Ben Goertzel [EMAIL PROTECTED] wrote: There was a DARPA program on transfer learning a few years back ... I believe I applied and got rejected (with perfect marks on the technical proposal, as usual ...) ... I never checked to see who got the $$ and what they did with it... See http://www.cs.utexas.edu/~mtaylor/Publications/AGI08-taylor.pdf Pei ben g On Sun, Nov 30, 2008 at 11:12 AM, Philip Hunt [EMAIL PROTECTED] wrote: 2008/11/30 Ben Goertzel [EMAIL PROTECTED]: Hi, I have proposed a problem domain called function predictor whose purpose is to allow an AI to learn across problem sub-domains, carrying its learning from one domain to another. (See http://www.includipedia.com/wiki/User:Cabalamat/Function_predictor ) I also think it would be useful if there was a regular (maybe annual) competition in the function predictor domain (or some similar domain). A bit like the Loebner Prize, except that it would be more useful to the advancement of AI, since the Loebner prize is silly. -- Philip Hunt, [EMAIL PROTECTED] How does that differ from what is generally called transfer learning ? I don't think it does differ. (Transfer learning is not a term I'd previously come across). -- Philip Hunt, [EMAIL PROTECTED] Please avoid sending me Word or PowerPoint attachments. See http://www.gnu.org/philosophy/no-word-attachments.html --- agi Archives: https://www.listbox.com/member/archive/303/=now RSS Feed: https://www.listbox.com/member/archive/rss/303/ Modify Your Subscription: https://www.listbox.com/member/?; Powered by Listbox: http://www.listbox.com -- Ben Goertzel, PhD CEO, Novamente LLC and Biomind LLC Director of Research, SIAI [EMAIL PROTECTED] I intend to live forever, or die trying. -- Groucho Marx --- agi Archives: https://www.listbox.com/member/archive/303/=now RSS Feed: https://www.listbox.com/member/archive/rss/303/ Modify Your Subscription: https://www.listbox.com/member/?; Powered by Listbox: http://www.listbox.com --- agi Archives: https://www.listbox.com/member/archive/303/=now RSS Feed: https://www.listbox.com/member/archive/rss/303/ Modify Your Subscription: https://www.listbox.com/member/?; Powered by Listbox: http://www.listbox.com agi | Archives | Modify Your Subscription --- agi Archives: https://www.listbox.com/member/archive/303/=now RSS Feed: https://www.listbox.com/member/archive/rss/303/ Modify Your Subscription: https://www.listbox.com/member/?member_id=8660244id_secret=120640061-aded06 Powered by Listbox: http://www.listbox.com
Re: [agi] AIXI (was: Mushed Up Decision Processes)
Philip Hunt wrote: 2008/11/29 Matt Mahoney [EMAIL PROTECTED]: The general problem of detecting overfitting is not computable. The principle according to Occam's Razor, formalized and proven by Hutter's AIXI model, is to choose the shortest program (simplest hypothesis) that generates the data. Overfitting is the case of choosing a program that is too large. Can someone explain AIXI to me? My understanding is that you've got some black-box process emitting output, and you generate all possible programs that emit the same output, then choose the shortest one. You then run this program and its subsequent output is what you predict the black-box process will do. This has the minor drawback, of course, that it requires infinite processing power and is therefore slightly impractical. I've read Hutter's paper Universal algorithmic intelligence, A mathematical top-down approach which amusingly describes itself as a gentle introduction to the AIXI model. Hutter also describes AIXItl of computation time Ord(t*2^L) where I assume L is the length of the program and I'm not sure what t is. Is AIXItl something that could be practically written or is it purely a theoretical construct? In short, is there something to AIXI or is it something I can safely ignore? It is something that, if you do not ignore it, will waste every second of brain cpu time that you devote to it ;-). Matt comes has a habit of repeating some version of the above statement ... according to Occam's Razor, [which was] formalized and proven by Hutter's AIXI model... on a semi-periodic basis. The first n times I took the trouble to explain why this statement is nonsense. Now I don't bother. AIXI is mathematical abstraction taken to the point of absurdity and beyond. By introducing infinite numbers of copies of all possible universes into your formalism, and by implying that functions can be computed on such structures, and by redefining common terms like intelligence to be abstractions based on that formalism, you can prove anything under the sun. That fact seems to escape some people. Richard Loosemore --- agi Archives: https://www.listbox.com/member/archive/303/=now RSS Feed: https://www.listbox.com/member/archive/rss/303/ Modify Your Subscription: https://www.listbox.com/member/?member_id=8660244id_secret=120640061-aded06 Powered by Listbox: http://www.listbox.com
Re: [agi] Mushed Up Decision Processes
Pei, Matt Taylor's work at Cycorp was not closely related to his published work at AGI-08. Matt contributed to a variety of other Transfer Learning tasks, and I cannot recall exactly what those were. -Steve Stephen L. Reed Artificial Intelligence Researcher http://texai.org/blog http://texai.org 3008 Oak Crest Ave. Austin, Texas, USA 78704 512.791.7860 From: Pei Wang [EMAIL PROTECTED] To: agi@v2.listbox.com Sent: Sunday, November 30, 2008 12:16:41 PM Subject: Re: [agi] Mushed Up Decision Processes Stephen, Does that mean what you did at Cycorp on transfer learning is similar to what Taylor presented to AGI-08? Pei On Sun, Nov 30, 2008 at 1:01 PM, Stephen Reed [EMAIL PROTECTED] wrote: Matt Taylor was also an intern at Cycorp where was on Cycorp's Transfer Learning team with me. -Steve Stephen L. Reed Artificial Intelligence Researcher http://texai.org/blog http://texai.org 3008 Oak Crest Ave. Austin, Texas, USA 78704 512.791.7860 From: Pei Wang [EMAIL PROTECTED] To: agi@v2.listbox.com Sent: Sunday, November 30, 2008 10:48:59 AM Subject: Re: [agi] Mushed Up Decision Processes On Sun, Nov 30, 2008 at 11:17 AM, Ben Goertzel [EMAIL PROTECTED] wrote: There was a DARPA program on transfer learning a few years back ... I believe I applied and got rejected (with perfect marks on the technical proposal, as usual ...) ... I never checked to see who got the $$ and what they did with it... See http://www.cs.utexas.edu/~mtaylor/Publications/AGI08-taylor.pdf Pei ben g On Sun, Nov 30, 2008 at 11:12 AM, Philip Hunt [EMAIL PROTECTED] wrote: 2008/11/30 Ben Goertzel [EMAIL PROTECTED]: Hi, I have proposed a problem domain called function predictor whose purpose is to allow an AI to learn across problem sub-domains, carrying its learning from one domain to another. (See http://www.includipedia.com/wiki/User:Cabalamat/Function_predictor ) I also think it would be useful if there was a regular (maybe annual) competition in the function predictor domain (or some similar domain). A bit like the Loebner Prize, except that it would be more useful to the advancement of AI, since the Loebner prize is silly. -- Philip Hunt, [EMAIL PROTECTED] How does that differ from what is generally called transfer learning ? I don't think it does differ. (Transfer learning is not a term I'd previously come across). -- Philip Hunt, [EMAIL PROTECTED] Please avoid sending me Word or PowerPoint attachments. See http://www.gnu.org/philosophy/no-word-attachments.html --- agi Archives: https://www.listbox.com/member/archive/303/=now RSS Feed: https://www.listbox.com/member/archive/rss/303/ Modify Your Subscription: https://www.listbox.com/member/?; Powered by Listbox: http://www.listbox.com -- Ben Goertzel, PhD CEO, Novamente LLC and Biomind LLC Director of Research, SIAI [EMAIL PROTECTED] I intend to live forever, or die trying. -- Groucho Marx --- agi Archives: https://www.listbox.com/member/archive/303/=now RSS Feed: https://www.listbox.com/member/archive/rss/303/ Modify Your Subscription: https://www.listbox.com/member/?; Powered by Listbox: http://www.listbox.com --- agi Archives: https://www.listbox.com/member/archive/303/=now RSS Feed: https://www.listbox.com/member/archive/rss/303/ Modify Your Subscription: https://www.listbox.com/member/?; Powered by Listbox: http://www.listbox.com agi | Archives | Modify Your Subscription --- agi Archives: https://www.listbox.com/member/archive/303/=now RSS Feed: https://www.listbox.com/member/archive/rss/303/ Modify Your Subscription: https://www.listbox.com/member/?; Powered by Listbox: http://www.listbox.com --- agi Archives: https://www.listbox.com/member/archive/303/=now RSS Feed: https://www.listbox.com/member/archive/rss/303/ Modify Your Subscription: https://www.listbox.com/member/?member_id=8660244id_secret=120640061-aded06 Powered by Listbox: http://www.listbox.com
Re: FW: [agi] A paper that actually does solve the problem of consciousness
Ed, Unfortunately to reply to your message in detail would absorb a lot of time, because there are two issues mixed up 1) you don't know much about computability theory, and educating you on it would take a lot of time (and is not best done on an email list) 2) I may not have expressed some of my weird philosophical ideas about computability and mind and reality clearly ... though Abram, at least, seemed to get them ;) [but he has a lot of background in the area] Just to clarify some simple things though: Pi is a computable number, because there's a program that would generate it if allowed to run long enough Also, pi has been proved irrational; and, quantum theory really has nothing directly to do with uncomputability... About How can several pounds of matter that is the human brain model the true complexity of an infinity of infinitely complexity things? it is certainly thinkable that the brain is infinite not finite in its information content, or that it's a sort of antenna that receives information from some infinite-information-content source. I'm not saying I believe this, just saying it's a logical possibility, and not really ruled out by available data... Your reply seems to assume that the brain is a finite computational system and that other alternatives don't make sense. I think this is an OK working assumption for AGI engineers but it's not proved by any means. My main point in that post was, simply, that science and language seem intrinsically unable to distinguish computable from uncomputable realities. That doesn't necessarily mean the latter don't exist but it means they're not really scientifically useful entities. But, my detailed argument in favor of this point requires some basic understanding of computability math to appreciate, and I can't review those basics in an email, it's too much... ben g On Sun, Nov 30, 2008 at 4:20 PM, Ed Porter [EMAIL PROTECTED] wrote: Ben, On November 19, 2008 5:39 you wrote the following under the above titled thread: -- Ed, I'd be curious for your reaction to http://multiverseaccordingtoben.blogspot.com/2008/10/are-uncomputable-entities-useless-forhtml which explores the limits of scientific and linguistic explanation, in a different but possibly related way to Richard's argument. -- In the below email I asked you some questions about your article, which capture my major problem in understanding it, and I don't think I ever receive a reply The questions were at the bottom of such a long post you may well never have even seen them. I know you are busy, but if you have time I would be interested in hearing your answers to the following questions about the following five quoted parts (shown in red if you are seeing this in rich text) from you article. If you are too busy to respond just say so, either on or off list. - (1) In the simplest case, A2 may represent U directly in the language, using a single expression How, can U be directly represented in the language if it is uncomputable? I assume you consider any irational number, such as pi to be uncomputable (although, at least pi has a forumula that with enough computation can approach it as a limit –I assume that for most real numbers if there is such a formula, we do not know it.) (By the way, do we know for a fact that pi is irational, and if so how do we know other than that we have caluclated it to millions of places and not yet found an exact solution?) Merely communicating the symbol pi only represents the number if the agent receiving the communication has a more detailed definition, but any definition, such as a formula for iteratively approaching pi, which presumably is what you mean by R_U would only be an approximation. So U could never by fully represented unless one had infinite time --- and I generally consider it a waste of time to think about infinate time unless there is something valuable about such considerations that has a use in much more human-sized chunks of time. In fact, it seems the major message of quantum mechanics is that even physical reality doesn't have the time or machinery to compute uncomputable things, like a space constructed of dimensions each correspond to all the real numbers within some astronomical range . So the real number line is not really real. It is at best a construct of the human mind that can at best only be approximated in part. (2) complexity(U) complexity(R_U) Because I did not understand how U could be represented, and how R_U could be anything other than an approximation for any practical purposes, I didn't understand the meaning of the above line from your article? If U and R_U have the meaning I guessed in my discussion of quote (1), then U could not be meaningfully representable in the language, other than by a symbol that references some definition
Re: [agi] Mushed Up Decision Processes
Ed, I think that we must rely on large collections of relatively simple patterns that are somehow capable of being mixed and used in interactions with the others. These interacting patterns (to use your term) would have extensive variations to make them flexible and useful with other patterns. When we learn that national housing prices did not provide us with the kind of detail that we needed we go and figure other ways to find data that showed some of the variations that would have helped us to prepare better for a situation like the one we are currently in. I was thinking of that exact example when I wrote about mushy decision making, because the national average price would be more mushy than the regional prices, or a multiple price level index. The mush index of an index does not mean that the index is garbage, but since something like this is derived from finer grained statistics, it really exemplifies the problem. My idea is that an agi program would have to go further than data mining. It would have to be able to shape its own use of statistics in order to establish validity for itself. I really feel that there is something really important about the classifiers of statistical methods that I just haven't grasped yet. My example for this this comes from statistics that are similar but just different enough so that they don't mesh quite right. Like two different marketing surveys that provide similar information which is so close that a marketer can draw conclusions from their combination but which aren't actually close enough to justify this process. Like asking different representative groups if they are planning to buy a television in one survey, and asking how much they think they will spend on appliances during the next two years. The two surveys are so close that you know the results can be combined, but they are so different that it is almost impossible to justify the combination in any reasonable way. If I could only figure this one out I think the other problems I am interested in would start to solve themselves. Jim Bromer On Sat, Nov 29, 2008 at 11:40 AM, Ed Porter [EMAIL PROTECTED] wrote: Jim My understanding is that a Novamente-like system would have a process of natural selection that tends to favor the retention and use of patterns (perceptive, cognative, behaviors) prove themselves useful in achieving goals in the word in which it is embodied. It seems to me t such a process of natural selection would tend to naturally put some sort of limit on how out-of-touch many of an AGI's patterns would be, at least with regard to patterns about things for which the AGI has had considerable experience from the world in which it is embodied. However, we humans often get pretty out of touch with real world probabilities, as the recent bubble in housing prices, and the commonly said, although historically inaccurate, statement of several years ago --- that housing prices never go down on a national --- shows. It would be helpful to make AGI's be a little more accurate in their evaluation of the evidence for many of their assumptions --- and what that evidence really says --- than we humans are. Ed Porter -Original Message- From: Jim Bromer [mailto:[EMAIL PROTECTED] Sent: Saturday, November 29, 2008 10:49 AM To: agi@v2.listbox.com Subject: [agi] Mushed Up Decision Processes One of the problems that comes with the casual use of analytical methods is that the user becomes inured to their habitual misuse. When a casual familiarity is combined with a habitual ignorance of the consequences of a misuse the user can become over-confident or unwisely dismissive of criticism regardless of how on the mark it might be. The most proper use of statistical and probabilistic methods is to base results on a strong association with the data that they were derived from. The problem is that the AI community cannot afford this strong a connection to original source because they are trying to emulate the mind in some way and it is not reasonable to assume that the mind is capable of storing all data that it has used to derive insight. This is a problem any AI method has to deal with, it is not just a probability thing. What is wrong with the AI-probability group mind-set is that very few of its proponents ever consider the problem of statistical ambiguity and its obvious consequences. All AI programmers have to consider the problem. Most theories about the mind posit the use of similar experiences to build up theories about the world (or to derive methods to deal effectively with the world). So even though the methods to deal with the data environment are detached from the original sources of those methods, they can still be reconnected by the examination of similar experiences that may subsequently occur. But still it is important to be able to recognize the significance and necessity of doing this from time to time. It is important to
Re: RE: FW: [agi] A paper that actually does solve the problem of consciousness
But quantum theory does appear to be directly related to limits of the computations of physical reality. The uncertainty theory and the quantization of quantum states are limitations on what can be computed by physical reality. Not really. They're limitations on what measurements of physical reality can be simultaneously made. Quantum systems can compute *exactly* the class of Turing computable functions ... this has been proved according to standard quantum mechanics math. however, there are some things they can compute faster than any Turing machine, in the average case but not the worst case. But, I am old fashioned enough to be more interested in things about the brain and AGI that are supported by what would traditionally be considered scientific evidence or by what can be reasoned or designed from such evidence. If there is any thing that would fit under those headings to support the notion of the brain either being infinite, or being an antenna that receives decodable information from some infinite-information-content source, I would love to hear it. the key point of the blog post you didn't fully grok, was a careful argument that (under certain, seemingly reasonable assumptions) science can never provide evidence in favor of infinite mechanisms... ben g --- agi Archives: https://www.listbox.com/member/archive/303/=now RSS Feed: https://www.listbox.com/member/archive/rss/303/ Modify Your Subscription: https://www.listbox.com/member/?member_id=8660244id_secret=120640061-aded06 Powered by Listbox: http://www.listbox.com
Re: RE: FW: [agi] A paper that actually does solve the problem of consciousness
On Mon, Dec 1, 2008 at 11:19 AM, Ed Porter [EMAIL PROTECTED] wrote: You said QUANTUM THEORY REALLY HAS NOTHING DIRECTLY TO DO WITH UNCOMPUTABILITY. Please don't quote people using this style, it hurts my eyes. But quantum theory does appear to be directly related to limits of the computations of physical reality. The uncertainty theory and the quantization of quantum states are limitations on what can be computed by physical reality. I don't even know what you're saying here. Maybe you're trying to say that it takes a really big computer to compute a very small box of physical reality.. which is true.. I just don't know why you would be saying that. You said IT IS CERTAINLY THINKABLE THAT THE BRAIN IS INFINITE NOT FINITE IN ITS INFORMATION CONTENT, OR THAT IT'S A SORT OF ANTENNA THAT RECEIVES INFORMATION FROM SOME INFINITE-INFORMATION-CONTENT SOURCE This certainly is thinkable. And that is a non-trivial statement. We should never forget that our concepts of reality could be nothing but illusions, and that our understanding of science and physical reality may be much more partial and flawed than we think. It's also completely unscientific. You might as well say that magic pixies deliver your thoughts from big invisible bucket made of gold. But, I am old fashioned enough to be more interested in things about the brain and AGI that are supported by what would traditionally be considered scientific evidence or by what can be reasoned or designed from such evidence. So why are you entertaining notions of magic antennas to God? If there is any thing that would fit under those headings to support the notion of the brain either being infinite, or being an antenna that receives decodable information from some infinite-information-content source, I would love to hear it. I wouldn't. It's untestable non-sense. Trent --- agi Archives: https://www.listbox.com/member/archive/303/=now RSS Feed: https://www.listbox.com/member/archive/rss/303/ Modify Your Subscription: https://www.listbox.com/member/?member_id=8660244id_secret=120640061-aded06 Powered by Listbox: http://www.listbox.com
RE: RE: FW: [agi] A paper that actually does solve the problem of consciousness
Regarding the uncertainty principal, Wikipedia says: In quantum physics, the Heisenberg uncertainty principle states that the values of certain pairs of conjugate variables (position and momentum, for instance) cannot both be known with arbitrary precision. That is, the more precisely one variable is known, the less precisely the other is known. THIS IS NOT A STATEMENT ABOUT THE LIMITATIONS OF A RESEARCHER'S ABILITY TO MEASURE PARTICULAR QUANTITIES OF A SYSTEM, BUT RATHER ABOUT THE NATURE OF THE SYSTEM ITSELF. (emphasis added.) I am sure you know more about quantum mechanics than I do. But I have heard many say the uncertainty controls limits not just on scientific measurement, but the amount of information different parts of reality can have about each other when computing in response to each other. Perhaps such theories are wrong, but they are not without support in the field. With regard to the statement science can never provide evidence in favor of infinite mechanisms I though you were saying there was no way the human mind could fully represent or fully understand an infinite mechanism --- which I agree with. You were correct in thinking that I did not grok that you were implying this means if an infinite mechanism exited there could be no evidence in favor of it infinity. In fact, it is not clear that this is the case, if you use provide evidence considerably more loosely than provide proof for. Until the advent of quantum mechanics and/or the theory of the expanding universe, based in part on observations and in part intuitions derived from them, many people felt the universe was infinitely continuous and/or of infinite extent in space and time. I agree you would probably never be able to prove infinite realities, but the mind is capable of conceiving of them, and of seeing evidence that might suggest to some their existence, such as was suggested to Einstein, who for many years I have been told believed in a universe that was infinite in time. Ed Porter -Original Message- From: Ben Goertzel [mailto:[EMAIL PROTECTED] Sent: Sunday, November 30, 2008 9:09 PM To: agi@v2.listbox.com Subject: Re: RE: FW: [agi] A paper that actually does solve the problem of consciousness But quantum theory does appear to be directly related to limits of the computations of physical reality. The uncertainty theory and the quantization of quantum states are limitations on what can be computed by physical reality. Not really. They're limitations on what measurements of physical reality can be simultaneously made. Quantum systems can compute *exactly* the class of Turing computable functions ... this has been proved according to standard quantum mechanics math. however, there are some things they can compute faster than any Turing machine, in the average case but not the worst case. But, I am old fashioned enough to be more interested in things about the brain and AGI that are supported by what would traditionally be considered scientific evidence or by what can be reasoned or designed from such evidence. If there is any thing that would fit under those headings to support the notion of the brain either being infinite, or being an antenna that receives decodable information from some infinite-information-content source, I would love to hear it. the key point of the blog post you didn't fully grok, was a careful argument that (under certain, seemingly reasonable assumptions) science can never provide evidence in favor of infinite mechanisms... ben g --- agi Archives: https://www.listbox.com/member/archive/303/=now RSS Feed: https://www.listbox.com/member/archive/rss/303/ Modify Your Subscription: https://www.listbox.com/member/?; Powered by Listbox: http://www.listbox.com --- agi Archives: https://www.listbox.com/member/archive/303/=now RSS Feed: https://www.listbox.com/member/archive/rss/303/ Modify Your Subscription: https://www.listbox.com/member/?member_id=8660244id_secret=120640061-aded06 Powered by Listbox: http://www.listbox.com
Re: RE: FW: [agi] A paper that actually does solve the problem of consciousness
HI, In quantum physics, the Heisenberg uncertainty principle states that the values of certain pairs of conjugate variables (position and momentum, for instance) cannot both be known with arbitrary precision. That is, the more precisely one variable is known, the less precisely the other is known. THIS IS NOT A STATEMENT ABOUT THE LIMITATIONS OF A RESEARCHER'S ABILITY TO MEASURE PARTICULAR QUANTITIES OF A SYSTEM, BUT RATHER ABOUT THE NATURE OF THE SYSTEM ITSELF. (emphasis added.) I am sure you know more about quantum mechanics than I do. But I have heard many say the uncertainty controls limits not just on scientific measurement, but the amount of information different parts of reality can have about each other when computing in response to each other. Perhaps such theories are wrong, but they are not without support in the field. Yeah, the interpretation of quantum theory is certainly contentious and there are multiple conflicting views... However, regarding quantum computing, it is universally agreed that the class of quantum computable functions is identical to the class of classically Turing computable functions. With regard to the statement science can never provide evidence in favor of infinite mechanisms I though you were saying there was no way the human mind could fully represent or fully understand an infinite mechanism --- which I agree with. No, I was not saying that there was no way the human mind could fully represent or fully understand an infinite mechanism What I argued is that **scientific data** can never convincingly be used to argue in favor of an infinite mechanism, due to the intrinsically finite nature of scientific data. This says **nothing** about any intrinsic limitations on the human mind ... unless one adds the axiom that the human mind must be entirely comprehensible via science ... which seems an unnecessary assumption to make In fact, it is not clear that this is the case, if you use provide evidence considerably more loosely than provide proof for. Until the advent of quantum mechanics and/or the theory of the expanding universe, based in part on observations and in part intuitions derived from them, many people felt the universe was infinitely continuous and/or of infinite extent in space and time. I agree you would probably never be able to prove infinite realities, but the mind is capable of conceiving of them, and of seeing evidence that might suggest to some their existence, such as was suggested to Einstein, who for many years I have been told believed in a universe that was infinite in time. well, my argument implies that you can never use science to prove that the mind is capable of conceiving of infinite realities This may be true in some other sense, but I argue, not in a scientific sense... -- Ben G --- agi Archives: https://www.listbox.com/member/archive/303/=now RSS Feed: https://www.listbox.com/member/archive/rss/303/ Modify Your Subscription: https://www.listbox.com/member/?member_id=8660244id_secret=120640061-aded06 Powered by Listbox: http://www.listbox.com
Re: RE: FW: [agi] A paper that actually does solve the problem of consciousness
OTOH, there is no possible real-world test to distinguish a true random sequence from a high-algorithmic-information quasi-random sequence So I don't find this argument very convincing... On Sun, Nov 30, 2008 at 10:42 PM, Hector Zenil [EMAIL PROTECTED] wrote: On Mon, Dec 1, 2008 at 3:09 AM, Ben Goertzel [EMAIL PROTECTED] wrote: But quantum theory does appear to be directly related to limits of the computations of physical reality. The uncertainty theory and the quantization of quantum states are limitations on what can be computed by physical reality. Not really. They're limitations on what measurements of physical reality can be simultaneously made. Quantum systems can compute *exactly* the class of Turing computable functions ... this has been proved according to standard quantum mechanics math. however, there are some things they can compute faster than any Turing machine, in the average case but not the worst case. Sorry, I am not really following the discussion but I just read that there is some misinterpretation here. It is the standard model of quantum computation that effectively computes exactly the Turing computable functions, but that was almost hand tailored to do so, perhaps because adding to the theory an assumption of continuum measurability was already too much (i.e. distinguishing infinitely close quantum states). But that is far from the claim that quantum systems can compute exactly the class of Turing computable functions. Actually the Hilbert space and the superposition of particles in an infinite number of states would suggest exactly the opposite. While the standard model of quantum computation only considers a superposition of 2 states (the so-called qubit, capable of entanglement in 0 and 1). But even if you stick to the standard model of quantum computation, the proof that it computes exactly the set of recursive functions [Feynman, Deutsch] can be put in jeopardy very easy : Turing machines are unable to produce non-deterministic randomness, something that quantum computers do as an intrinsic property of quantum mechanics (not only because of measure limitations of the kind of the Heisenberg principle but by quantum non-locality, i.e. the violation of Bell's theorem). I just exhibited a non-Turing computable function that standard quantum computers compute... [Calude, Casti] But, I am old fashioned enough to be more interested in things about the brain and AGI that are supported by what would traditionally be considered scientific evidence or by what can be reasoned or designed from such evidence. If there is any thing that would fit under those headings to support the notion of the brain either being infinite, or being an antenna that receives decodable information from some infinite-information-content source, I would love to hear it. You and/or other people might be interested in a paper of mine published some time ago on the possible computational power of the human mind and the way to encode infinite information in the brain: http://arxiv.org/abs/cs/0605065 the key point of the blog post you didn't fully grok, was a careful argument that (under certain, seemingly reasonable assumptions) science can never provide evidence in favor of infinite mechanisms... ben g --- agi Archives: https://www.listbox.com/member/archive/303/=now RSS Feed: https://www.listbox.com/member/archive/rss/303/ Modify Your Subscription: https://www.listbox.com/member/?; Powered by Listbox: http://www.listbox.com -- Hector Zenilhttp://www.mathrix.org --- agi Archives: https://www.listbox.com/member/archive/303/=now RSS Feed: https://www.listbox.com/member/archive/rss/303/ Modify Your Subscription: https://www.listbox.com/member/?; Powered by Listbox: http://www.listbox.com -- Ben Goertzel, PhD CEO, Novamente LLC and Biomind LLC Director of Research, SIAI [EMAIL PROTECTED] I intend to live forever, or die trying. -- Groucho Marx --- agi Archives: https://www.listbox.com/member/archive/303/=now RSS Feed: https://www.listbox.com/member/archive/rss/303/ Modify Your Subscription: https://www.listbox.com/member/?member_id=8660244id_secret=120640061-aded06 Powered by Listbox: http://www.listbox.com
Re: RE: FW: [agi] A paper that actually does solve the problem of consciousness
On Mon, Dec 1, 2008 at 3:09 AM, Ben Goertzel [EMAIL PROTECTED] wrote: But quantum theory does appear to be directly related to limits of the computations of physical reality. The uncertainty theory and the quantization of quantum states are limitations on what can be computed by physical reality. Not really. They're limitations on what measurements of physical reality can be simultaneously made. Quantum systems can compute *exactly* the class of Turing computable functions ... this has been proved according to standard quantum mechanics math. however, there are some things they can compute faster than any Turing machine, in the average case but not the worst case. Sorry, I am not really following the discussion but I just read that there is some misinterpretation here. It is the standard model of quantum computation that effectively computes exactly the Turing computable functions, but that was almost hand tailored to do so, perhaps because adding to the theory an assumption of continuum measurability was already too much (i.e. distinguishing infinitely close quantum states). But that is far from the claim that quantum systems can compute exactly the class of Turing computable functions. Actually the Hilbert space and the superposition of particles in an infinite number of states would suggest exactly the opposite. While the standard model of quantum computation only considers a superposition of 2 states (the so-called qubit, capable of entanglement in 0 and 1). But even if you stick to the standard model of quantum computation, the proof that it computes exactly the set of recursive functions [Feynman, Deutsch] can be put in jeopardy very easy : Turing machines are unable to produce non-deterministic randomness, something that quantum computers do as an intrinsic property of quantum mechanics (not only because of measure limitations of the kind of the Heisenberg principle but by quantum non-locality, i.e. the violation of Bell's theorem). I just exhibited a non-Turing computable function that standard quantum computers compute... [Calude, Casti] But, I am old fashioned enough to be more interested in things about the brain and AGI that are supported by what would traditionally be considered scientific evidence or by what can be reasoned or designed from such evidence. If there is any thing that would fit under those headings to support the notion of the brain either being infinite, or being an antenna that receives decodable information from some infinite-information-content source, I would love to hear it. You and/or other people might be interested in a paper of mine published some time ago on the possible computational power of the human mind and the way to encode infinite information in the brain: http://arxiv.org/abs/cs/0605065 the key point of the blog post you didn't fully grok, was a careful argument that (under certain, seemingly reasonable assumptions) science can never provide evidence in favor of infinite mechanisms... ben g --- agi Archives: https://www.listbox.com/member/archive/303/=now RSS Feed: https://www.listbox.com/member/archive/rss/303/ Modify Your Subscription: https://www.listbox.com/member/?; Powered by Listbox: http://www.listbox.com -- Hector Zenilhttp://www.mathrix.org --- agi Archives: https://www.listbox.com/member/archive/303/=now RSS Feed: https://www.listbox.com/member/archive/rss/303/ Modify Your Subscription: https://www.listbox.com/member/?member_id=8660244id_secret=120640061-aded06 Powered by Listbox: http://www.listbox.com
Re: RE: FW: [agi] A paper that actually does solve the problem of consciousness
On Mon, Dec 1, 2008 at 4:44 AM, Ben Goertzel [EMAIL PROTECTED] wrote: OTOH, there is no possible real-world test to distinguish a true random sequence from a high-algorithmic-information quasi-random sequence I know, but the point is not whether we can distinguish it, but that quantum mechanics actually predicts to be intrinsically capable of non-deterministic randomness, while for a Turing machine that is impossible by definition. I find quite convincing and interesting the way in which the mathematical proof of the standard model of quantum computation as Turing computable has been put in jeopardy by physical reality. So I don't find this argument very convincing... On Sun, Nov 30, 2008 at 10:42 PM, Hector Zenil [EMAIL PROTECTED] wrote: On Mon, Dec 1, 2008 at 3:09 AM, Ben Goertzel [EMAIL PROTECTED] wrote: But quantum theory does appear to be directly related to limits of the computations of physical reality. The uncertainty theory and the quantization of quantum states are limitations on what can be computed by physical reality. Not really. They're limitations on what measurements of physical reality can be simultaneously made. Quantum systems can compute *exactly* the class of Turing computable functions ... this has been proved according to standard quantum mechanics math. however, there are some things they can compute faster than any Turing machine, in the average case but not the worst case. Sorry, I am not really following the discussion but I just read that there is some misinterpretation here. It is the standard model of quantum computation that effectively computes exactly the Turing computable functions, but that was almost hand tailored to do so, perhaps because adding to the theory an assumption of continuum measurability was already too much (i.e. distinguishing infinitely close quantum states). But that is far from the claim that quantum systems can compute exactly the class of Turing computable functions. Actually the Hilbert space and the superposition of particles in an infinite number of states would suggest exactly the opposite. While the standard model of quantum computation only considers a superposition of 2 states (the so-called qubit, capable of entanglement in 0 and 1). But even if you stick to the standard model of quantum computation, the proof that it computes exactly the set of recursive functions [Feynman, Deutsch] can be put in jeopardy very easy : Turing machines are unable to produce non-deterministic randomness, something that quantum computers do as an intrinsic property of quantum mechanics (not only because of measure limitations of the kind of the Heisenberg principle but by quantum non-locality, i.e. the violation of Bell's theorem). I just exhibited a non-Turing computable function that standard quantum computers compute... [Calude, Casti] But, I am old fashioned enough to be more interested in things about the brain and AGI that are supported by what would traditionally be considered scientific evidence or by what can be reasoned or designed from such evidence. If there is any thing that would fit under those headings to support the notion of the brain either being infinite, or being an antenna that receives decodable information from some infinite-information-content source, I would love to hear it. You and/or other people might be interested in a paper of mine published some time ago on the possible computational power of the human mind and the way to encode infinite information in the brain: http://arxiv.org/abs/cs/0605065 the key point of the blog post you didn't fully grok, was a careful argument that (under certain, seemingly reasonable assumptions) science can never provide evidence in favor of infinite mechanisms... ben g --- agi Archives: https://www.listbox.com/member/archive/303/=now RSS Feed: https://www.listbox.com/member/archive/rss/303/ Modify Your Subscription: https://www.listbox.com/member/?; Powered by Listbox: http://www.listbox.com -- Hector Zenilhttp://www.mathrix.org --- agi Archives: https://www.listbox.com/member/archive/303/=now RSS Feed: https://www.listbox.com/member/archive/rss/303/ Modify Your Subscription: https://www.listbox.com/member/?; Powered by Listbox: http://www.listbox.com -- Ben Goertzel, PhD CEO, Novamente LLC and Biomind LLC Director of Research, SIAI [EMAIL PROTECTED] I intend to live forever, or die trying. -- Groucho Marx --- agi Archives: https://www.listbox.com/member/archive/303/=now RSS Feed: https://www.listbox.com/member/archive/rss/303/ Modify Your Subscription: https://www.listbox.com/member/?; Powered by Listbox: http://www.listbox.com -- Hector Zenilhttp://www.mathrix.org
Re: RE: FW: [agi] A paper that actually does solve the problem of consciousness
On Mon, Dec 1, 2008 at 4:53 AM, Hector Zenil [EMAIL PROTECTED] wrote: On Mon, Dec 1, 2008 at 4:44 AM, Ben Goertzel [EMAIL PROTECTED] wrote: OTOH, there is no possible real-world test to distinguish a true random sequence from a high-algorithmic-information quasi-random sequence I know, but the point is not whether we can distinguish it, but that quantum mechanics actually predicts to be intrinsically capable of non-deterministic randomness, while for a Turing machine that is impossible by definition. I find quite convincing and interesting the way in which the mathematical proof of the standard model of quantum computation as Turing computable has been put in jeopardy by physical reality. or at least by a model of physical reality... =) (a reality by the way, that the authors of the mathematical proof believe in as the most basic) So I don't find this argument very convincing... On Sun, Nov 30, 2008 at 10:42 PM, Hector Zenil [EMAIL PROTECTED] wrote: On Mon, Dec 1, 2008 at 3:09 AM, Ben Goertzel [EMAIL PROTECTED] wrote: But quantum theory does appear to be directly related to limits of the computations of physical reality. The uncertainty theory and the quantization of quantum states are limitations on what can be computed by physical reality. Not really. They're limitations on what measurements of physical reality can be simultaneously made. Quantum systems can compute *exactly* the class of Turing computable functions ... this has been proved according to standard quantum mechanics math. however, there are some things they can compute faster than any Turing machine, in the average case but not the worst case. Sorry, I am not really following the discussion but I just read that there is some misinterpretation here. It is the standard model of quantum computation that effectively computes exactly the Turing computable functions, but that was almost hand tailored to do so, perhaps because adding to the theory an assumption of continuum measurability was already too much (i.e. distinguishing infinitely close quantum states). But that is far from the claim that quantum systems can compute exactly the class of Turing computable functions. Actually the Hilbert space and the superposition of particles in an infinite number of states would suggest exactly the opposite. While the standard model of quantum computation only considers a superposition of 2 states (the so-called qubit, capable of entanglement in 0 and 1). But even if you stick to the standard model of quantum computation, the proof that it computes exactly the set of recursive functions [Feynman, Deutsch] can be put in jeopardy very easy : Turing machines are unable to produce non-deterministic randomness, something that quantum computers do as an intrinsic property of quantum mechanics (not only because of measure limitations of the kind of the Heisenberg principle but by quantum non-locality, i.e. the violation of Bell's theorem). I just exhibited a non-Turing computable function that standard quantum computers compute... [Calude, Casti] But, I am old fashioned enough to be more interested in things about the brain and AGI that are supported by what would traditionally be considered scientific evidence or by what can be reasoned or designed from such evidence. If there is any thing that would fit under those headings to support the notion of the brain either being infinite, or being an antenna that receives decodable information from some infinite-information-content source, I would love to hear it. You and/or other people might be interested in a paper of mine published some time ago on the possible computational power of the human mind and the way to encode infinite information in the brain: http://arxiv.org/abs/cs/0605065 the key point of the blog post you didn't fully grok, was a careful argument that (under certain, seemingly reasonable assumptions) science can never provide evidence in favor of infinite mechanisms... ben g --- agi Archives: https://www.listbox.com/member/archive/303/=now RSS Feed: https://www.listbox.com/member/archive/rss/303/ Modify Your Subscription: https://www.listbox.com/member/?; Powered by Listbox: http://www.listbox.com -- Hector Zenilhttp://www.mathrix.org --- agi Archives: https://www.listbox.com/member/archive/303/=now RSS Feed: https://www.listbox.com/member/archive/rss/303/ Modify Your Subscription: https://www.listbox.com/member/?; Powered by Listbox: http://www.listbox.com -- Ben Goertzel, PhD CEO, Novamente LLC and Biomind LLC Director of Research, SIAI [EMAIL PROTECTED] I intend to live forever, or die trying. -- Groucho Marx --- agi Archives: https://www.listbox.com/member/archive/303/=now RSS Feed:
Re: RE: FW: [agi] A paper that actually does solve the problem of consciousness
But I don't get your point at all, because the whole idea of nondeterministic randomness has nothing to do with physical reality... true random numbers are uncomputable entities which can never be existed, and any finite series of observations can be modeled equally well as the first N bits of an uncomputable series or of a computable one... ben g On Sun, Nov 30, 2008 at 10:53 PM, Hector Zenil [EMAIL PROTECTED] wrote: On Mon, Dec 1, 2008 at 4:44 AM, Ben Goertzel [EMAIL PROTECTED] wrote: OTOH, there is no possible real-world test to distinguish a true random sequence from a high-algorithmic-information quasi-random sequence I know, but the point is not whether we can distinguish it, but that quantum mechanics actually predicts to be intrinsically capable of non-deterministic randomness, while for a Turing machine that is impossible by definition. I find quite convincing and interesting the way in which the mathematical proof of the standard model of quantum computation as Turing computable has been put in jeopardy by physical reality. So I don't find this argument very convincing... On Sun, Nov 30, 2008 at 10:42 PM, Hector Zenil [EMAIL PROTECTED] wrote: On Mon, Dec 1, 2008 at 3:09 AM, Ben Goertzel [EMAIL PROTECTED] wrote: But quantum theory does appear to be directly related to limits of the computations of physical reality. The uncertainty theory and the quantization of quantum states are limitations on what can be computed by physical reality. Not really. They're limitations on what measurements of physical reality can be simultaneously made. Quantum systems can compute *exactly* the class of Turing computable functions ... this has been proved according to standard quantum mechanics math. however, there are some things they can compute faster than any Turing machine, in the average case but not the worst case. Sorry, I am not really following the discussion but I just read that there is some misinterpretation here. It is the standard model of quantum computation that effectively computes exactly the Turing computable functions, but that was almost hand tailored to do so, perhaps because adding to the theory an assumption of continuum measurability was already too much (i.e. distinguishing infinitely close quantum states). But that is far from the claim that quantum systems can compute exactly the class of Turing computable functions. Actually the Hilbert space and the superposition of particles in an infinite number of states would suggest exactly the opposite. While the standard model of quantum computation only considers a superposition of 2 states (the so-called qubit, capable of entanglement in 0 and 1). But even if you stick to the standard model of quantum computation, the proof that it computes exactly the set of recursive functions [Feynman, Deutsch] can be put in jeopardy very easy : Turing machines are unable to produce non-deterministic randomness, something that quantum computers do as an intrinsic property of quantum mechanics (not only because of measure limitations of the kind of the Heisenberg principle but by quantum non-locality, i.e. the violation of Bell's theorem). I just exhibited a non-Turing computable function that standard quantum computers compute... [Calude, Casti] But, I am old fashioned enough to be more interested in things about the brain and AGI that are supported by what would traditionally be considered scientific evidence or by what can be reasoned or designed from such evidence. If there is any thing that would fit under those headings to support the notion of the brain either being infinite, or being an antenna that receives decodable information from some infinite-information-content source, I would love to hear it. You and/or other people might be interested in a paper of mine published some time ago on the possible computational power of the human mind and the way to encode infinite information in the brain: http://arxiv.org/abs/cs/0605065 the key point of the blog post you didn't fully grok, was a careful argument that (under certain, seemingly reasonable assumptions) science can never provide evidence in favor of infinite mechanisms... ben g --- agi Archives: https://www.listbox.com/member/archive/303/=now RSS Feed: https://www.listbox.com/member/archive/rss/303/ Modify Your Subscription: https://www.listbox.com/member/?; Powered by Listbox: http://www.listbox.com -- Hector Zenilhttp://www.mathrix.org --- agi Archives: https://www.listbox.com/member/archive/303/=now RSS Feed: https://www.listbox.com/member/archive/rss/303/ Modify Your Subscription: https://www.listbox.com/member/?; Powered by Listbox: http://www.listbox.com -- Ben Goertzel, PhD CEO, Novamente LLC and Biomind LLC Director of Research, SIAI [EMAIL PROTECTED] I
Re: RE: FW: [agi] A paper that actually does solve the problem of consciousness
On Mon, Dec 1, 2008 at 4:55 AM, Ben Goertzel [EMAIL PROTECTED] wrote: But I don't get your point at all, because the whole idea of nondeterministic randomness has nothing to do with physical reality... It has all to do when it is about quantum mechanics. Quantum mechanics is non-deterministic by nature. A quantum computer, even within the standard model of quantum computation, could then take advantage of this intrinsic property of the physical (quantum) reality (assuming the model correct, as most physicists would). true random numbers are uncomputable entities which can never be existed, and any finite series of observations can be modeled equally well as the first N bits of an uncomputable series or of a computable one... That's the point, that's what the classical theory of computability would say (also making some assumptions, namely Church's thesis), but again quantum mechanics says something else : The fact that quantum computers are able of non-deterministic randomness by definition and Turing machines are unable of non-deterministic randomness also by definition seems incompatible with the claim (or mathematical proof) that standard quantum computers compute exactly the same functions than Turing machines, and that's only when dealing with standard quantum computation, because non-standard quantum computation is far from being proved to be reduced to Turing-computable (modulo their speed-up). Concerning the observations, you don't need to do an infinite number of them to get a non-computable answer from an Oracle (although you would need in case you want to finitely verify it). And even if you can model equally well the first N bits of a non-deterministic random sequence, the fact that a random sequence is ontologically of a non-deterministic nature, makes it a priori a different one in essence from a pseudo random sequence. The point is not epistemological. In any case, whether we agree on the philosophical matter, my point is that it is not the case that there is a mathematical proof about quantum systems computing exactly the same functions than Turing machines. There is a mathematical proof that the standard model of quantum computation computes the same set of functions than Turing machines. ben g On Sun, Nov 30, 2008 at 10:53 PM, Hector Zenil [EMAIL PROTECTED] wrote: On Mon, Dec 1, 2008 at 4:44 AM, Ben Goertzel [EMAIL PROTECTED] wrote: OTOH, there is no possible real-world test to distinguish a true random sequence from a high-algorithmic-information quasi-random sequence I know, but the point is not whether we can distinguish it, but that quantum mechanics actually predicts to be intrinsically capable of non-deterministic randomness, while for a Turing machine that is impossible by definition. I find quite convincing and interesting the way in which the mathematical proof of the standard model of quantum computation as Turing computable has been put in jeopardy by physical reality. So I don't find this argument very convincing... On Sun, Nov 30, 2008 at 10:42 PM, Hector Zenil [EMAIL PROTECTED] wrote: On Mon, Dec 1, 2008 at 3:09 AM, Ben Goertzel [EMAIL PROTECTED] wrote: But quantum theory does appear to be directly related to limits of the computations of physical reality. The uncertainty theory and the quantization of quantum states are limitations on what can be computed by physical reality. Not really. They're limitations on what measurements of physical reality can be simultaneously made. Quantum systems can compute *exactly* the class of Turing computable functions ... this has been proved according to standard quantum mechanics math. however, there are some things they can compute faster than any Turing machine, in the average case but not the worst case. Sorry, I am not really following the discussion but I just read that there is some misinterpretation here. It is the standard model of quantum computation that effectively computes exactly the Turing computable functions, but that was almost hand tailored to do so, perhaps because adding to the theory an assumption of continuum measurability was already too much (i.e. distinguishing infinitely close quantum states). But that is far from the claim that quantum systems can compute exactly the class of Turing computable functions. Actually the Hilbert space and the superposition of particles in an infinite number of states would suggest exactly the opposite. While the standard model of quantum computation only considers a superposition of 2 states (the so-called qubit, capable of entanglement in 0 and 1). But even if you stick to the standard model of quantum computation, the proof that it computes exactly the set of recursive functions [Feynman, Deutsch] can be put in jeopardy very easy : Turing machines are unable to produce non-deterministic randomness, something that quantum computers do as an intrinsic property of quantum mechanics (not only because of
Re: RE: FW: [agi] A paper that actually does solve the problem of consciousness
On Mon, Dec 1, 2008 at 4:55 AM, Ben Goertzel [EMAIL PROTECTED] wrote: But I don't get your point at all, because the whole idea of nondeterministic randomness has nothing to do with physical reality... I don't get it. You don't think that quantum mechanics is part of our physical reality (if it is not all of it)? true random numbers are uncomputable entities which can never be existed, you can say that either they don't exist or they do exist but that we don't have access to them. That's a rather philosophical matter. But scientifically QM says the latter. Even more, since bits from a non-deterministic random source are truly independent from each other, something that does not happen when produced by a Turing machine, then any sequence (even finite) is of different nature from one produced by a Turing machine. In practice, if your claim is that you will not be able to distinguish the difference, you actually would if you let the machine run for a longer period of time, once finished its physical resources it will either halt or start over (making the random string periodic), while QM says that resources don't matter, a quantum computer will always continue producing non-deterministic (e.g. never periodic) strings of any length independently of any constraint of time or space! and any finite series of observations can be modeled equally well as the first N bits of an uncomputable series or of a computable one... ben g On Sun, Nov 30, 2008 at 10:53 PM, Hector Zenil [EMAIL PROTECTED] wrote: On Mon, Dec 1, 2008 at 4:44 AM, Ben Goertzel [EMAIL PROTECTED] wrote: OTOH, there is no possible real-world test to distinguish a true random sequence from a high-algorithmic-information quasi-random sequence I know, but the point is not whether we can distinguish it, but that quantum mechanics actually predicts to be intrinsically capable of non-deterministic randomness, while for a Turing machine that is impossible by definition. I find quite convincing and interesting the way in which the mathematical proof of the standard model of quantum computation as Turing computable has been put in jeopardy by physical reality. So I don't find this argument very convincing... On Sun, Nov 30, 2008 at 10:42 PM, Hector Zenil [EMAIL PROTECTED] wrote: On Mon, Dec 1, 2008 at 3:09 AM, Ben Goertzel [EMAIL PROTECTED] wrote: But quantum theory does appear to be directly related to limits of the computations of physical reality. The uncertainty theory and the quantization of quantum states are limitations on what can be computed by physical reality. Not really. They're limitations on what measurements of physical reality can be simultaneously made. Quantum systems can compute *exactly* the class of Turing computable functions ... this has been proved according to standard quantum mechanics math. however, there are some things they can compute faster than any Turing machine, in the average case but not the worst case. Sorry, I am not really following the discussion but I just read that there is some misinterpretation here. It is the standard model of quantum computation that effectively computes exactly the Turing computable functions, but that was almost hand tailored to do so, perhaps because adding to the theory an assumption of continuum measurability was already too much (i.e. distinguishing infinitely close quantum states). But that is far from the claim that quantum systems can compute exactly the class of Turing computable functions. Actually the Hilbert space and the superposition of particles in an infinite number of states would suggest exactly the opposite. While the standard model of quantum computation only considers a superposition of 2 states (the so-called qubit, capable of entanglement in 0 and 1). But even if you stick to the standard model of quantum computation, the proof that it computes exactly the set of recursive functions [Feynman, Deutsch] can be put in jeopardy very easy : Turing machines are unable to produce non-deterministic randomness, something that quantum computers do as an intrinsic property of quantum mechanics (not only because of measure limitations of the kind of the Heisenberg principle but by quantum non-locality, i.e. the violation of Bell's theorem). I just exhibited a non-Turing computable function that standard quantum computers compute... [Calude, Casti] But, I am old fashioned enough to be more interested in things about the brain and AGI that are supported by what would traditionally be considered scientific evidence or by what can be reasoned or designed from such evidence. If there is any thing that would fit under those headings to support the notion of the brain either being infinite, or being an antenna that receives decodable information from some infinite-information-content source, I would love to hear it. You and/or other people might be interested in a paper of mine published some
Re: RE: FW: [agi] A paper that actually does solve the problem of consciousness
On Sun, Nov 30, 2008 at 11:48 PM, Hector Zenil [EMAIL PROTECTED] wrote: On Mon, Dec 1, 2008 at 4:55 AM, Ben Goertzel [EMAIL PROTECTED] wrote: But I don't get your point at all, because the whole idea of nondeterministic randomness has nothing to do with physical reality... I don't get it. You don't think that quantum mechanics is part of our physical reality (if it is not all of it)? Of course it isn't -- quantum mechanics is a mathematical and conceptual model that we use in order to predict certain finite sets of finite-precision observations, based on other such sets true random numbers are uncomputable entities which can never be existed, you can say that either they don't exist or they do exist but that we don't have access to them. That's a rather philosophical matter. But scientifically QM says the latter. Sure it does: but there is an equivalent mathematical theory that explains all observations identically to QM, yet doesn't posit any uncomputable entities So, choosing to posit that these uncomputable entities exist in reality, is just a matter of aesthetic or philosophical taste ... so you can't really say they exist in reality, because they contribute nothing to the predictive power of QM ... -- Ben G --- agi Archives: https://www.listbox.com/member/archive/303/=now RSS Feed: https://www.listbox.com/member/archive/rss/303/ Modify Your Subscription: https://www.listbox.com/member/?member_id=8660244id_secret=120640061-aded06 Powered by Listbox: http://www.listbox.com
Re: RE: FW: [agi] A paper that actually does solve the problem of consciousness
On Mon, Dec 1, 2008 at 6:20 AM, Ben Goertzel [EMAIL PROTECTED] wrote: On Sun, Nov 30, 2008 at 11:48 PM, Hector Zenil [EMAIL PROTECTED] wrote: On Mon, Dec 1, 2008 at 4:55 AM, Ben Goertzel [EMAIL PROTECTED] wrote: But I don't get your point at all, because the whole idea of nondeterministic randomness has nothing to do with physical reality... I don't get it. You don't think that quantum mechanics is part of our physical reality (if it is not all of it)? Of course it isn't -- quantum mechanics is a mathematical and conceptual model that we use in order to predict certain finite sets of finite-precision observations, based on other such sets Oh I see! I think that's of philosophical taste as well. I don't think everybody would agree with you. Specially if you poll physicists like those that constructed the standard model of computation! We cannot ask Feynman, but I actually asked Deutsch. He does not only think QM is our most basic physical reality (he thinks math and computer science lie in quantum mechanics), but he even takes quite seriously his theory of parallel universes! and he is not alone. Speaking by myself, I would agree with you, but I think we would need to relativize the concept of agreement. I don't think QM is just another model of merely mathematical value to make finite predictions. I think physical models say something about our physical reality. If you deny QM as part of our physical reality then I guess you deny any other physical model. I wonder then what is left to you. You perhaps would embrace total skepticism, perhaps even solipsism. Current trends have moved from there to a more relativized positions, where models are considered so, models, but still with some value as part of our actual physical reality (just as Newtonian physics is not just completely wrong after General Relativity since it still describes a huge part of our physical reality). At the end, even if you claim a Platonic physical reality to which we have no access at all, not even through our best explanations in the way of models, the world is either quantum or not (as we have defined the theory), and as long as it remains as our best explanation of a the phenomena that characterizes one has to face it to other models describing other aspects or models of our best known physical reality. It is not clear to me how you would deny the physical reality of QM but defend the theory of computability or algorithmic information theory as if they were more basic than QM. If we take as equally basic QM and AIT, even in a practical sense, there are incompatibilities in essence. QM cannot be said as Turing computable, and AIT cannot posit the in-existence of non-deterministic randomness specially when QM says something else. I am more in the side of AIT but I think the question is open, is interesting (both philosophically and scientific) and not trivial at all. true random numbers are uncomputable entities which can never be existed, you can say that either they don't exist or they do exist but that we don't have access to them. That's a rather philosophical matter. But scientifically QM says the latter. Sure it does: but there is an equivalent mathematical theory that explains all observations identically to QM, yet doesn't posit any uncomputable entities So, choosing to posit that these uncomputable entities exist in reality, is just a matter of aesthetic or philosophical taste ... so you can't really say they exist in reality, because they contribute nothing to the predictive power of QM ... There are people that think that quantum randomness is actually the source of the complexity we see in the universe [Bennett, Lloyd]. Even when I do not agree with them (since AIT does not require non-deterministic randomness) I think it is not that trivial since even researchers think they contribute in some fundamental (not only philosophical) way. -- Ben G --- agi Archives: https://www.listbox.com/member/archive/303/=now RSS Feed: https://www.listbox.com/member/archive/rss/303/ Modify Your Subscription: https://www.listbox.com/member/?; Powered by Listbox: http://www.listbox.com -- Hector Zenilhttp://www.mathrix.org --- agi Archives: https://www.listbox.com/member/archive/303/=now RSS Feed: https://www.listbox.com/member/archive/rss/303/ Modify Your Subscription: https://www.listbox.com/member/?member_id=8660244id_secret=120640061-aded06 Powered by Listbox: http://www.listbox.com
Re: [agi] Mushed Up Decision Processes
On Nov 30, 2008, at 7:31 AM, Philip Hunt wrote: 2008/11/30 Ben Goertzel [EMAIL PROTECTED]: In general, the standard AI methods can't handle pattern recognition problems requiring finding complex interdependencies among multiple variables that are obscured among scads of other variables The human mind seems to do this via building up intuition via drawing analogies among multiple problems it confronts during its history. Yes, so that people learn one problem, then it helps them to learn other similar ones. Is there any AI software that does this? I'm not aware of any. To do this as a practical matter, you need to address *at least* two well-known hard-but-important unsolved algorithm problems in completely different areas of theoretical computer science that have nothing to do with AI per se. That is no small hurdle, even if you are a bloody genius. That said, I doubt most AI researchers could even tell you what those two big problems are which is, obliquely, the other part of the problem. I have proposed a problem domain called function predictor whose purpose is to allow an AI to learn across problem sub-domains, carrying its learning from one domain to another. (See http://www.includipedia.com/wiki/User:Cabalamat/Function_predictor ) In Feder/Merhav/Gutman's 1995 Reflections on... followup to their 1992 paper on universal sequence prediction, they make the observation, which can be found at the following link, that it is probably useful to introduce the concept of prediction error complexity as an important metric which is similar to what you are talking about in the theoretical abstract: http://www.itsoc.org/review/meir/node5.html Our understanding of this area is better in 2008 than it was in 1995, but this is one of the earliest serious references to the idea in a theoretical way. Somewhat obscure and primitive by current standards, but influential in the AIXI and related flavors of AI theory based on computational information theory. Or at least, I found it very interesting and useful a decade ago. Cheers, J. Andrew Rogers --- agi Archives: https://www.listbox.com/member/archive/303/=now RSS Feed: https://www.listbox.com/member/archive/rss/303/ Modify Your Subscription: https://www.listbox.com/member/?member_id=8660244id_secret=120640061-aded06 Powered by Listbox: http://www.listbox.com
Re: RE: FW: [agi] A paper that actually does solve the problem of consciousness
Hector Zenil wrote: On Mon, Dec 1, 2008 at 6:20 AM, Ben Goertzel [EMAIL PROTECTED] wrote: On Sun, Nov 30, 2008 at 11:48 PM, Hector Zenil [EMAIL PROTECTED] wrote: On Mon, Dec 1, 2008 at 4:55 AM, Ben Goertzel [EMAIL PROTECTED] wrote: But I don't get your point at all, because the whole idea of ... ... Oh I see! I think that's of philosophical taste as well. I don't think everybody would agree with you. Specially if you poll physicists like those that constructed the standard model of computation! We cannot ask Feynman, but I actually asked Deutsch. He does not only think QM is our most basic physical reality (he thinks math and computer science lie in quantum mechanics), but he even takes quite seriously his theory of parallel universes! and he is not alone. Speaking by... when I do not agree with them (since AIT does not require non-deterministic randomness) I think it is not that trivial since even researchers think they contribute in some fundamental (not only philosophical) way. -- Ben G Still, one must remember that there is Quantum Theory, and then there are the interpretations of Quantum Theory. As I understand things there are still several models of the universe which yield the same observables, and choosing between them is a matter of taste. They are all totally consistent with standard Quantum Theory...but ...well, which do you prefer? Multi-world? Action at a distance? No objective universe? (I'm not sure what that means.) The present is created by the future as well as the past? As I understand things, these cannot be chosen between on the basis of Quantum Theory. And somewhere in that mix is Wholeness and the Implicate Order. When math gets translated into Language, interpretations add things. --- agi Archives: https://www.listbox.com/member/archive/303/=now RSS Feed: https://www.listbox.com/member/archive/rss/303/ Modify Your Subscription: https://www.listbox.com/member/?member_id=8660244id_secret=120640061-aded06 Powered by Listbox: http://www.listbox.com
