Re: [agi] creativity
Ben, I'm glad that you have decided to respond to, - or at least recognize - my criticisms/points re creativity, because they are extremely important and central to AGI - & as I said, it isn't just you but everyone who is avoiding them - when it is in all your interests to confront them *now*/*urgently*. I think in fact my criticisms do hold - but obviously I will have to look at your book first. [I may have looked at it already - I've read quite a bit of you - but you've written a lot]. If you could link me, or send me a copy, I will reply in a more considered way. ... some loose ends in reply to a message from a few days back ... Mike Tintner wrote: *** Be honest - when and where have you ever addressed creative problems? [Just count how many problems I have raised).. *** In my 1997 book FROM COMPLEXITY TO CREATIVITY *** Just as it is obvious that I know next to nothing about programming, it is also obvious that you have v. little experience of discussing creative problemsolving - at, I stress, a *metacognitive* level. (And nor, AFAIK, do any AGI-ers - only partly excepting Minsky). *** The 1997 book I referenced above in fact contains a significant amount of metacognition about creativity. You seem to have the idea that it's supposed to be possible to explain an AGI's creative process in detail, in specific instances ... and I don't know why you think that, since it's not even the case for humans. *** All this stands in total, stark contrast to any discussion of logical or mathematical, problems, where you are always delighted to engage in detail, and v. helpful and constructive - and do not make excuses to cover up your inexperience. *** Aspects of the mind that are closer to the deliberative, intensely conscious level are easier to discuss explicitly and in detail. Aspects of the mind that are mainly unconscious and have to do mainly with the coordinated activity of a large number of different processes, are harder to describe in detail in specific instances. One can describe the underlying processes but this then becomes technical and lengthy!! -- Ben -- Ben Goertzel, PhD CEO, Novamente LLC and Biomind LLC Director of Research, SIAI [EMAIL PROTECTED] "Nothing will ever be attempted if all possible objections must be first overcome " - Dr Samuel Johnson -- 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=8660244&id_secret=117534816-b15a34 Powered by Listbox: http://www.listbox.com
[agi] two types of semantics [Was: NARS and probability]
A brief and non-technical description of the two types of semantics mentioned in the previous discussions: (1) Model-Theoretic Semantics (MTS) (1.1) There is a world existing independently outside the intelligent system (human or machine). (1.2) In principle, there is an objective description of the world, in terms of objects, their properties, and relations among them. (1.3) Within the intelligent system, its knowledge is an approximation of the objective description of the world. (1.4) The meaning of a symbol within the system is the object it refers to in the world. (1.5) The truth-value of a statement within the system measures how close it approximates the fact in the world. (2) Experience-Grounded Semantics (EGS) (2.1) There is a world existing independently outside the intelligent system (human or machine). [same as (1.1), but the agreement stops here] (2.2) Even in principle, there is no objective description of the world. What the system has is its experience, the history of its interaction of the world. (2.3) Within the intelligent system, its knowledge is a summary of its experience. (2.4) The meaning of a symbol within the system is determined by its role in the experience. (2.5) The truth-value of a statement within the system measures how close it summarizes the relevant part of the experience. To further simplify the description, in the context of learning and reasoning: MTS takes "objective truth" of statements and "real meaning" of terms as aim of approximation, while EGS refuses them, but takes experience (input data) as the only thing to depend on. As usual, each theory has its strength and limitation. The issue is which one is more proper for AGI. MTS has been dominating in math, logic, and computer science, and therefore is accepted by the majority people. Even so, it has been attacked by other people (not only the EGS believers) for many reasons. A while ago I made a figure to illustrate this difference, which is at http://nars.wang.googlepages.com/wang.semantics-figure.pdf . A manifesto of EGS is at http://nars.wang.googlepages.com/wang.semantics.pdf Since the debate on the nature of "truth" and "meaning" has existed for thousands of years, I don't think we can settle down it here by some email exchanges. I just want to let the interested people know the theoretical background of the related discussions. Pei On Sat, Oct 11, 2008 at 8:34 PM, Ben Goertzel <[EMAIL PROTECTED]> wrote: > > > > Hi, > >> >> > What this highlights for me is the idea that NARS truth values attempt >> > to reflect the evidence so far, while probabilities attempt to reflect >> > the world > > I agree that probabilities attempt to reflect the world > >> >> . >> >> Well said. This is exactly the difference between an >> experience-grounded semantics and a model-theoretic semantics. > > I don't agree with this distinction ... unless you are construing "model > theoretic semantics" in a very restrictive way, which then does not apply to > PLN. > > If by model-theoretic semantics you mean something like what Wikipedia says > at http://en.wikipedia.org/wiki/Formal_semantics, > > *** > Model-theoretic semantics is the archetype of Alfred Tarski's semantic > theory of truth, based on his T-schema, and is one of the founding concepts > of model theory. This is the most widespread approach, and is based on the > idea that the meaning of the various parts of the propositions are given by > the possible ways we can give a recursively specified group of > interpretation functions from them to some predefined mathematical domains: > an interpretation of first-order predicate logic is given by a mapping from > terms to a universe of individuals, and a mapping from propositions to the > truth values "true" and "false". > *** > > then yes, PLN's semantics is based on a mapping from terms to a universe of > individuals, and a mapping from propositions to truth values. On the other > hand, these "individuals" may be for instance **elementary sensations or > actions**, rather than higher-level individuals like, say, a specific cat, > or the concept "cat". So there is nothing non-experience-based about > mapping terms into a "individuals" that are the system's direct experience > ... and then building up more abstract terms by grouping these > directly-experience-based terms. > > IMO, the dichotomy between experience-based and model-based semantics is a > misleading one. Model-based semantics has often been used in a > non-experience-based way, but that is not because it fundamentally **has** > to be used in that way. > > To say that PLN tries to model the world, is then just to say that it tries > to make probabilistic predictions about sensations and actions that have not > yet been experienced ... which is certainly the case. > >> >> Once >> again, the difference in truth-value functions is reduced to the >> difference in semantics, what is, what the "truth-value" attempts to >> measure. > > Agreed... > > Be
Re: [agi] two types of semantics [Was: NARS and probability]
Thanks Pei, I would add (for others, obviously you know this stuff) that there are many different theoretical justifications of probability theory, hence that the use of probability theory does not imply model-theoretic semantics nor any other particular approach to semantics. My own philosophy is even further from your summary of model-theoretic semantics than it is from (my reading of) Tarski's original version of model theoretic semantics. I am not an objectivist whatsoever (I read too many Oriental philosophy books in my early youth, when my mom was studying for her PhD in Chinese history, and my brain was even more pliant ;-). I deal extensively with objectivity/subjectivity/intersubjectivity issues in "The Hidden Pattern." As an example, if one justifies probability theory according a Cox's-axioms approach, no model theory is necessary. In this approach, it is justified as a set of a priori constraints that the system chooses to impose on its own reasoning. In a de Finetti approach, it is justified because the system wants to be able to "win bets" with other agents. The intersection between this notion and the hypothesis of an "objective world" is unclear, but it's not obvious why these hypothetical agents need to have objective existence. As you say, this is a deep philosophical rat's-nest... my point is just that it's not correct to imply "probability theory = traditional model theoretic semantics" -- Ben G On Sun, Oct 12, 2008 at 8:29 AM, Pei Wang <[EMAIL PROTECTED]> wrote: > A brief and non-technical description of the two types of semantics > mentioned in the previous discussions: > > (1) Model-Theoretic Semantics (MTS) > > (1.1) There is a world existing independently outside the intelligent > system (human or machine). > > (1.2) In principle, there is an objective description of the world, in > terms of objects, their properties, and relations among them. > > (1.3) Within the intelligent system, its knowledge is an approximation > of the objective description of the world. > > (1.4) The meaning of a symbol within the system is the object it > refers to in the world. > > (1.5) The truth-value of a statement within the system measures how > close it approximates the fact in the world. > > (2) Experience-Grounded Semantics (EGS) > > (2.1) There is a world existing independently outside the intelligent > system (human or machine). [same as (1.1), but the agreement stops > here] > > (2.2) Even in principle, there is no objective description of the > world. What the system has is its experience, the history of its > interaction of the world. > > (2.3) Within the intelligent system, its knowledge is a summary of its > experience. > > (2.4) The meaning of a symbol within the system is determined by its > role in the experience. > > (2.5) The truth-value of a statement within the system measures how > close it summarizes the relevant part of the experience. > > To further simplify the description, in the context of learning and > reasoning: MTS takes "objective truth" of statements and "real > meaning" of terms as aim of approximation, while EGS refuses them, but > takes experience (input data) as the only thing to depend on. > > As usual, each theory has its strength and limitation. The issue is > which one is more proper for AGI. MTS has been dominating in math, > logic, and computer science, and therefore is accepted by the majority > people. Even so, it has been attacked by other people (not only the > EGS believers) for many reasons. > > A while ago I made a figure to illustrate this difference, which is at > http://nars.wang.googlepages.com/wang.semantics-figure.pdf . A > manifesto of EGS is at > http://nars.wang.googlepages.com/wang.semantics.pdf > > Since the debate on the nature of "truth" and "meaning" has existed > for thousands of years, I don't think we can settle down it here by > some email exchanges. I just want to let the interested people know > the theoretical background of the related discussions. > > Pei > > > On Sat, Oct 11, 2008 at 8:34 PM, Ben Goertzel <[EMAIL PROTECTED]> wrote: > > > > > > > > Hi, > > > >> > >> > What this highlights for me is the idea that NARS truth values attempt > >> > to reflect the evidence so far, while probabilities attempt to reflect > >> > the world > > > > I agree that probabilities attempt to reflect the world > > > >> > >> . > >> > >> Well said. This is exactly the difference between an > >> experience-grounded semantics and a model-theoretic semantics. > > > > I don't agree with this distinction ... unless you are construing "model > > theoretic semantics" in a very restrictive way, which then does not apply > to > > PLN. > > > > If by model-theoretic semantics you mean something like what Wikipedia > says > > at http://en.wikipedia.org/wiki/Formal_semantics, > > > > *** > > Model-theoretic semantics is the archetype of Alfred Tarski's semantic > > theory of truth, based on his T-schema, and is one of the founding > concepts > > o
Re: [agi] two types of semantics [Was: NARS and probability]
Ben, Of course, "probability theory", in its mathematical form, is not bounded to any semantics at all, though it implicitly exclude some possibilities. A semantic theory is associated to it when probability theory is applied to a practical situation. There are several major schools in the interpretation of probability (see http://plato.stanford.edu/entries/probability-interpret/), and their relations with NARS is explained in Section 8.5.1 of my book. As for the interpretation of probability in PLN, I'd rather wait for your book than to make comment based on your brief explanation. Pei On Sun, Oct 12, 2008 at 9:13 AM, Ben Goertzel <[EMAIL PROTECTED]> wrote: > > Thanks Pei, > > I would add (for others, obviously you know this stuff) that there are many > different > theoretical justifications of probability theory, hence that the use of > probability > theory does not imply model-theoretic semantics nor any other particular > approach to semantics. > > My own philosophy is even further from your summary of model-theoretic > semantics than it is from (my reading of) Tarski's original version of model > theoretic semantics. I am not an objectivist whatsoever (I read too > many > Oriental philosophy books in my early youth, when my mom was studying > for her PhD in Chinese history, and my brain was even more pliant ;-). > I deal extensively with objectivity/subjectivity/intersubjectivity issues in > "The Hidden Pattern." > > As an example, if one justifies probability theory according a Cox's-axioms > approach, no model theory is necessary. In this approach, it is justified > as a set of a priori constraints that the system chooses to impose on its > own > reasoning. > > In a de Finetti approach, it is justified because the system wants to > be able to "win bets" with other agents. The intersection between this > notion and the hypothesis of an "objective world" is unclear, but it's not > obvious why these hypothetical agents need to have objective existence. > > As you say, this is a deep philosophical rat's-nest... my point is just that > it's > not correct to imply "probability theory = traditional > model theoretic semantics" > > -- Ben G > > On Sun, Oct 12, 2008 at 8:29 AM, Pei Wang <[EMAIL PROTECTED]> wrote: >> >> A brief and non-technical description of the two types of semantics >> mentioned in the previous discussions: >> >> (1) Model-Theoretic Semantics (MTS) >> >> (1.1) There is a world existing independently outside the intelligent >> system (human or machine). >> >> (1.2) In principle, there is an objective description of the world, in >> terms of objects, their properties, and relations among them. >> >> (1.3) Within the intelligent system, its knowledge is an approximation >> of the objective description of the world. >> >> (1.4) The meaning of a symbol within the system is the object it >> refers to in the world. >> >> (1.5) The truth-value of a statement within the system measures how >> close it approximates the fact in the world. >> >> (2) Experience-Grounded Semantics (EGS) >> >> (2.1) There is a world existing independently outside the intelligent >> system (human or machine). [same as (1.1), but the agreement stops >> here] >> >> (2.2) Even in principle, there is no objective description of the >> world. What the system has is its experience, the history of its >> interaction of the world. >> >> (2.3) Within the intelligent system, its knowledge is a summary of its >> experience. >> >> (2.4) The meaning of a symbol within the system is determined by its >> role in the experience. >> >> (2.5) The truth-value of a statement within the system measures how >> close it summarizes the relevant part of the experience. >> >> To further simplify the description, in the context of learning and >> reasoning: MTS takes "objective truth" of statements and "real >> meaning" of terms as aim of approximation, while EGS refuses them, but >> takes experience (input data) as the only thing to depend on. >> >> As usual, each theory has its strength and limitation. The issue is >> which one is more proper for AGI. MTS has been dominating in math, >> logic, and computer science, and therefore is accepted by the majority >> people. Even so, it has been attacked by other people (not only the >> EGS believers) for many reasons. >> >> A while ago I made a figure to illustrate this difference, which is at >> http://nars.wang.googlepages.com/wang.semantics-figure.pdf . A >> manifesto of EGS is at >> http://nars.wang.googlepages.com/wang.semantics.pdf >> >> Since the debate on the nature of "truth" and "meaning" has existed >> for thousands of years, I don't think we can settle down it here by >> some email exchanges. I just want to let the interested people know >> the theoretical background of the related discussions. >> >> Pei >> >> >> On Sat, Oct 11, 2008 at 8:34 PM, Ben Goertzel <[EMAIL PROTECTED]> wrote: >> > >> > >> > >> > Hi, >> > >> >> >> >> > What this highlights for me is the idea that NARS
Re: [agi] open or closed source for AGI project?
On Sun, Oct 12, 2008 at 1:32 AM, YKY (Yan King Yin) < [EMAIL PROTECTED]> wrote: > On Sun, Oct 12, 2008 at 12:56 PM, Ben Goertzel <[EMAIL PROTECTED]> wrote: > > > OpenCog has VariableNodes in the AtomTable, which are used to represent > > variables in the sense of FOL ... > > I'm still unclear as to how OC performs inference with variables, > unification, etc. Maybe you can explain that during a tutorial > session? Are your questions about the math level, or the code level? Only Ari Heljakka understands exactly how the current PLN code does that stuff ... but Joel is figuring it out, and will I'm sure be happy to explain it once he does ;-) OTOH, I can explain it on the mathematical and conceptual level... > > The sentential approach is more classical and helps me think more > clearly about optimization issues (ie inference control), which is a > big unsolved problem. I think the biggest issues w/ inference control are more than the "cognitive science" or algorithmics level than the implementation level, hence independent of the choice of a sentential vs. hypergraph knowledge representation... The next couple Wed. night OpenCog tutorial/discussion sessions will focus on inference, and one will focus on inference control specifically... 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=8660244&id_secret=117534816-b15a34 Powered by Listbox: http://www.listbox.com
Re: [agi] creativity
Mike, A very messily formatted rough draft of From Complexity to Creativity is here http://www.goertzel.org/books/complex/contents.html Alas I long ago lost the wordperfect 5.1 file that was used to generate the final proofs way back when... The chapter that gives an overall theory of the psychology of creativity is here http://www.goertzel.org/books/complex/ch14.html however that chapter is very high level and to make it concrete you'd need to trace the foundations of the ideas there back into the prior chapters... Here is the intro text of that chapter ... some of it sounds like it could have come out of your own mouth ;-) * Creativity is the great mystery at the center of Western culture. We preach order, science, logic and reason. But none of the great accomplishments of science, logic and reason was actually achieved in a scientific, logical, reasonable manner. Every single one must, instead, be attributed to the strange, obscure and definitively irrational process of creative inspiration. Logic and reason are indispensible in the working out ideas, once they have arisen -- but the actual * conception* of bold, original ideas is something else entirely. No creative person completely understands what they do when they create. And no two individuals' incomplete accounts of creative process would be the same. But nevertheless, there are some common patterns spanning different people's creativity; and there is thus some basis for theory. In previous chapters, the phenomenon of creativity has lurked around the edges of the discussion. Here I will confront it head-on. Drawing on the ideas of most of the previous chapters, I will frame a comprehensive complexity-theoretic answer to the question: How do those most exquisitely complex systems, minds, go about creating forms? I will begin on the whole-mind, personality level, with the idea that certain individuals possess creatively-inspired, largely medium-dependent "creative subselves." In conjunction with the Fundamental Principle of Personality Dynamics, this idea in itself gives new insight into the much-discussed relationship between inspired creativity and madness. A healthy creative person, it is argued, maintains I-You relationships between their creative subselves and their everyday subselves. In the mind of a "mad" creative person, on the other hand, the relationship is strained and competitive, in the I-It mold. The question of the * internal workings* of the creative subself is then addressed. Different complex systems models are viewed as capturing different * aspects* of the creative process. First, the analogy between creative thought and the genetic algorithm is pursued. It is argued that the creative process involves two main aspects: combination and mutation of ideas, in the spirit of the genetic algorithm; and analogical spreading of ideas, following the lines of the dynamically self-organizing associative memory network. The dual network model explains the interconnection of these two processes. While these processes are present throughout the mind, creative subselves provide an environment in which they are allowed to act with unusual liberty and flexibility. This flexibility is related to the action of the perceptual-cognitive loop, which, when "coherentizing" thought-systems within the creative subself, seems to have a particularly gentle hand, creating systems that can relatively easily be dissected and put back together in new ways. Other subselves create their own realities having to do with physical sense-perceptions and actions; creative subselves, on the other hand, create their own realities having to do with abstract forms and structures. Because the creative subself deals with a more flexible "environment," with a more amenable fitness landscape, it can afford to be more flexible internally. In dynamical systems terms, the process of creative thought may be viewed as the simultaneous creation and exploration of autopoietic attractors. Ideas are explored, and allowed to lead to other ideas, in trajectories that evolve in parallel. Eventually this dynamic process leads to a kind of rough "convergence" on a strange attractor -- a basic sense for what kind of idea, what kind of product one is going to have. The various parts of this attractor are then explored in a basically chaotic way, until a particular * part* of the attractor is converged to. In formal language terms, we may express this by saingy that the act of creative inspiration *creates its own languages *, which it then narrows down into simpler and simpler languages, until it arrives at languages that the rest of the mind can understand. The hierarchical structure of the dual network plays a role here, in that attractors formed on higher levels progressively give rise to attractors dealing with lower levels. One thus has a kind of iterative substitution, similar to the L-system model of sentence production. Instea
Re: AW: [agi] I Can't Be In Two Places At Once.
I think it's normal for tempers to flare during a depression. This kind of technology really pays for itself. The only thing that matters is the code Eric B On 10/12/08, Ben Goertzel <[EMAIL PROTECTED]> wrote: > No idea, Mentifex ... I haven't filtered out any of your messages (or > anyone's) ... but sometimes messages get held up at listbox.com by their > automated spam filters (or for other random reasons) and I take too long to > log in there and approve them... > > ben > > >> > >> >> Well, how come my posts aren't getting through? (Going out >> to the list) What do you call that? >> >> ATM/Mentifex >> -- >> http://code.google.com/p/mindforth/ >> > > > > -- > Ben Goertzel, PhD > CEO, Novamente LLC and Biomind LLC > Director of Research, SIAI > [EMAIL PROTECTED] > > "Nothing will ever be attempted if all possible objections must be first > overcome " - Dr Samuel Johnson > > > > --- > 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=8660244&id_secret=117534816-b15a34 Powered by Listbox: http://www.listbox.com
Re: [agi] two types of semantics [Was: NARS and probability]
Pei, In this context, how do you justify the use of 'k'? It seems like, by introducing 'k', you add a reliance on the truth of the future "after k observations" into the semantics. Since the induction/abduction formula is dependent on 'k', the truth values that result no longer only summarize experience; they are calculated with prediction in mind. --Abram On Sun, Oct 12, 2008 at 8:29 AM, Pei Wang <[EMAIL PROTECTED]> wrote: > A brief and non-technical description of the two types of semantics > mentioned in the previous discussions: > > (1) Model-Theoretic Semantics (MTS) > > (1.1) There is a world existing independently outside the intelligent > system (human or machine). > > (1.2) In principle, there is an objective description of the world, in > terms of objects, their properties, and relations among them. > > (1.3) Within the intelligent system, its knowledge is an approximation > of the objective description of the world. > > (1.4) The meaning of a symbol within the system is the object it > refers to in the world. > > (1.5) The truth-value of a statement within the system measures how > close it approximates the fact in the world. > > (2) Experience-Grounded Semantics (EGS) > > (2.1) There is a world existing independently outside the intelligent > system (human or machine). [same as (1.1), but the agreement stops > here] > > (2.2) Even in principle, there is no objective description of the > world. What the system has is its experience, the history of its > interaction of the world. > > (2.3) Within the intelligent system, its knowledge is a summary of its > experience. > > (2.4) The meaning of a symbol within the system is determined by its > role in the experience. > > (2.5) The truth-value of a statement within the system measures how > close it summarizes the relevant part of the experience. > > To further simplify the description, in the context of learning and > reasoning: MTS takes "objective truth" of statements and "real > meaning" of terms as aim of approximation, while EGS refuses them, but > takes experience (input data) as the only thing to depend on. > > As usual, each theory has its strength and limitation. The issue is > which one is more proper for AGI. MTS has been dominating in math, > logic, and computer science, and therefore is accepted by the majority > people. Even so, it has been attacked by other people (not only the > EGS believers) for many reasons. > > A while ago I made a figure to illustrate this difference, which is at > http://nars.wang.googlepages.com/wang.semantics-figure.pdf . A > manifesto of EGS is at > http://nars.wang.googlepages.com/wang.semantics.pdf > > Since the debate on the nature of "truth" and "meaning" has existed > for thousands of years, I don't think we can settle down it here by > some email exchanges. I just want to let the interested people know > the theoretical background of the related discussions. > > Pei > > > On Sat, Oct 11, 2008 at 8:34 PM, Ben Goertzel <[EMAIL PROTECTED]> wrote: >> >> >> >> Hi, >> >>> >>> > What this highlights for me is the idea that NARS truth values attempt >>> > to reflect the evidence so far, while probabilities attempt to reflect >>> > the world >> >> I agree that probabilities attempt to reflect the world >> >>> >>> . >>> >>> Well said. This is exactly the difference between an >>> experience-grounded semantics and a model-theoretic semantics. >> >> I don't agree with this distinction ... unless you are construing "model >> theoretic semantics" in a very restrictive way, which then does not apply to >> PLN. >> >> If by model-theoretic semantics you mean something like what Wikipedia says >> at http://en.wikipedia.org/wiki/Formal_semantics, >> >> *** >> Model-theoretic semantics is the archetype of Alfred Tarski's semantic >> theory of truth, based on his T-schema, and is one of the founding concepts >> of model theory. This is the most widespread approach, and is based on the >> idea that the meaning of the various parts of the propositions are given by >> the possible ways we can give a recursively specified group of >> interpretation functions from them to some predefined mathematical domains: >> an interpretation of first-order predicate logic is given by a mapping from >> terms to a universe of individuals, and a mapping from propositions to the >> truth values "true" and "false". >> *** >> >> then yes, PLN's semantics is based on a mapping from terms to a universe of >> individuals, and a mapping from propositions to truth values. On the other >> hand, these "individuals" may be for instance **elementary sensations or >> actions**, rather than higher-level individuals like, say, a specific cat, >> or the concept "cat". So there is nothing non-experience-based about >> mapping terms into a "individuals" that are the system's direct experience >> ... and then building up more abstract terms by grouping these >> directly-experience-based terms. >> >> IMO, the dichotomy between experience-based and model-bas
Re: [agi] two types of semantics [Was: NARS and probability]
Abram: The parameter 'k' does not really depend on the future, because it makes no assumption about what will happen in that period of time. It is just a "ruler" or "weight" (used with scale) to measure the amount of evidence, as a "reference amount". For other people: The definition of confidence c = w/(w+k) states that confidence is the proportion of current evidence among future evidence, after the coming of evidence of amount k. Pei On Sun, Oct 12, 2008 at 1:48 PM, Abram Demski <[EMAIL PROTECTED]> wrote: > Pei, > > In this context, how do you justify the use of 'k'? It seems like, by > introducing 'k', you add a reliance on the truth of the future "after > k observations" into the semantics. Since the induction/abduction > formula is dependent on 'k', the truth values that result no longer > only summarize experience; they are calculated with prediction in > mind. > > --Abram > > On Sun, Oct 12, 2008 at 8:29 AM, Pei Wang <[EMAIL PROTECTED]> wrote: >> A brief and non-technical description of the two types of semantics >> mentioned in the previous discussions: >> >> (1) Model-Theoretic Semantics (MTS) >> >> (1.1) There is a world existing independently outside the intelligent >> system (human or machine). >> >> (1.2) In principle, there is an objective description of the world, in >> terms of objects, their properties, and relations among them. >> >> (1.3) Within the intelligent system, its knowledge is an approximation >> of the objective description of the world. >> >> (1.4) The meaning of a symbol within the system is the object it >> refers to in the world. >> >> (1.5) The truth-value of a statement within the system measures how >> close it approximates the fact in the world. >> >> (2) Experience-Grounded Semantics (EGS) >> >> (2.1) There is a world existing independently outside the intelligent >> system (human or machine). [same as (1.1), but the agreement stops >> here] >> >> (2.2) Even in principle, there is no objective description of the >> world. What the system has is its experience, the history of its >> interaction of the world. >> >> (2.3) Within the intelligent system, its knowledge is a summary of its >> experience. >> >> (2.4) The meaning of a symbol within the system is determined by its >> role in the experience. >> >> (2.5) The truth-value of a statement within the system measures how >> close it summarizes the relevant part of the experience. >> >> To further simplify the description, in the context of learning and >> reasoning: MTS takes "objective truth" of statements and "real >> meaning" of terms as aim of approximation, while EGS refuses them, but >> takes experience (input data) as the only thing to depend on. >> >> As usual, each theory has its strength and limitation. The issue is >> which one is more proper for AGI. MTS has been dominating in math, >> logic, and computer science, and therefore is accepted by the majority >> people. Even so, it has been attacked by other people (not only the >> EGS believers) for many reasons. >> >> A while ago I made a figure to illustrate this difference, which is at >> http://nars.wang.googlepages.com/wang.semantics-figure.pdf . A >> manifesto of EGS is at >> http://nars.wang.googlepages.com/wang.semantics.pdf >> >> Since the debate on the nature of "truth" and "meaning" has existed >> for thousands of years, I don't think we can settle down it here by >> some email exchanges. I just want to let the interested people know >> the theoretical background of the related discussions. >> >> Pei >> >> >> On Sat, Oct 11, 2008 at 8:34 PM, Ben Goertzel <[EMAIL PROTECTED]> wrote: >>> >>> >>> >>> Hi, >>> > What this highlights for me is the idea that NARS truth values attempt > to reflect the evidence so far, while probabilities attempt to reflect > the world >>> >>> I agree that probabilities attempt to reflect the world >>> . Well said. This is exactly the difference between an experience-grounded semantics and a model-theoretic semantics. >>> >>> I don't agree with this distinction ... unless you are construing "model >>> theoretic semantics" in a very restrictive way, which then does not apply to >>> PLN. >>> >>> If by model-theoretic semantics you mean something like what Wikipedia says >>> at http://en.wikipedia.org/wiki/Formal_semantics, >>> >>> *** >>> Model-theoretic semantics is the archetype of Alfred Tarski's semantic >>> theory of truth, based on his T-schema, and is one of the founding concepts >>> of model theory. This is the most widespread approach, and is based on the >>> idea that the meaning of the various parts of the propositions are given by >>> the possible ways we can give a recursively specified group of >>> interpretation functions from them to some predefined mathematical domains: >>> an interpretation of first-order predicate logic is given by a mapping from >>> terms to a universe of individuals, and a mapping from propositions to the >>> truth values "true" and "false". >
Re: [agi] two types of semantics [Was: NARS and probability]
On the other hand, in PLN's indefinite probabilities there is a parameter k which plays a similar mathematical role, yet **is** explicitly interpreted as being about a "number of hypothetical future observations" ... Clearly the interplay btw algebra and interpretation is one of the things that makes this area of research (uncertain logic) "interesting" ... ben g On Sun, Oct 12, 2008 at 2:07 PM, Pei Wang <[EMAIL PROTECTED]> wrote: > Abram: The parameter 'k' does not really depend on the future, because > it makes no assumption about what will happen in that period of time. > It is just a "ruler" or "weight" (used with scale) to measure the > amount of evidence, as a "reference amount". > > For other people: The definition of confidence c = w/(w+k) states that > confidence is the proportion of current evidence among future > evidence, after the coming of evidence of amount k. > > Pei > > On Sun, Oct 12, 2008 at 1:48 PM, Abram Demski <[EMAIL PROTECTED]> > wrote: > > Pei, > > > > In this context, how do you justify the use of 'k'? It seems like, by > > introducing 'k', you add a reliance on the truth of the future "after > > k observations" into the semantics. Since the induction/abduction > > formula is dependent on 'k', the truth values that result no longer > > only summarize experience; they are calculated with prediction in > > mind. > > > > --Abram > > > > On Sun, Oct 12, 2008 at 8:29 AM, Pei Wang <[EMAIL PROTECTED]> > wrote: > >> A brief and non-technical description of the two types of semantics > >> mentioned in the previous discussions: > >> > >> (1) Model-Theoretic Semantics (MTS) > >> > >> (1.1) There is a world existing independently outside the intelligent > >> system (human or machine). > >> > >> (1.2) In principle, there is an objective description of the world, in > >> terms of objects, their properties, and relations among them. > >> > >> (1.3) Within the intelligent system, its knowledge is an approximation > >> of the objective description of the world. > >> > >> (1.4) The meaning of a symbol within the system is the object it > >> refers to in the world. > >> > >> (1.5) The truth-value of a statement within the system measures how > >> close it approximates the fact in the world. > >> > >> (2) Experience-Grounded Semantics (EGS) > >> > >> (2.1) There is a world existing independently outside the intelligent > >> system (human or machine). [same as (1.1), but the agreement stops > >> here] > >> > >> (2.2) Even in principle, there is no objective description of the > >> world. What the system has is its experience, the history of its > >> interaction of the world. > >> > >> (2.3) Within the intelligent system, its knowledge is a summary of its > >> experience. > >> > >> (2.4) The meaning of a symbol within the system is determined by its > >> role in the experience. > >> > >> (2.5) The truth-value of a statement within the system measures how > >> close it summarizes the relevant part of the experience. > >> > >> To further simplify the description, in the context of learning and > >> reasoning: MTS takes "objective truth" of statements and "real > >> meaning" of terms as aim of approximation, while EGS refuses them, but > >> takes experience (input data) as the only thing to depend on. > >> > >> As usual, each theory has its strength and limitation. The issue is > >> which one is more proper for AGI. MTS has been dominating in math, > >> logic, and computer science, and therefore is accepted by the majority > >> people. Even so, it has been attacked by other people (not only the > >> EGS believers) for many reasons. > >> > >> A while ago I made a figure to illustrate this difference, which is at > >> http://nars.wang.googlepages.com/wang.semantics-figure.pdf . A > >> manifesto of EGS is at > >> http://nars.wang.googlepages.com/wang.semantics.pdf > >> > >> Since the debate on the nature of "truth" and "meaning" has existed > >> for thousands of years, I don't think we can settle down it here by > >> some email exchanges. I just want to let the interested people know > >> the theoretical background of the related discussions. > >> > >> Pei > >> > >> > >> On Sat, Oct 11, 2008 at 8:34 PM, Ben Goertzel <[EMAIL PROTECTED]> wrote: > >>> > >>> > >>> > >>> Hi, > >>> > > > What this highlights for me is the idea that NARS truth values > attempt > > to reflect the evidence so far, while probabilities attempt to > reflect > > the world > >>> > >>> I agree that probabilities attempt to reflect the world > >>> > > . > > Well said. This is exactly the difference between an > experience-grounded semantics and a model-theoretic semantics. > >>> > >>> I don't agree with this distinction ... unless you are construing > "model > >>> theoretic semantics" in a very restrictive way, which then does not > apply to > >>> PLN. > >>> > >>> If by model-theoretic semantics you mean something like what Wikipedia > says > >>> at http://en.wikipedia.org/wiki/Formal_semant
Re: [agi] two types of semantics [Was: NARS and probability]
True. Similar parameters can be found in the work of Carnap and Walley, with different interpretations. Pei On Sun, Oct 12, 2008 at 2:11 PM, Ben Goertzel <[EMAIL PROTECTED]> wrote: > > On the other hand, in PLN's indefinite probabilities there is a parameter k > which > plays a similar mathematical role, yet **is** explicitly interpreted as > being about > a "number of hypothetical future observations" ... > > Clearly the interplay btw algebra and interpretation is one of the things > that makes > this area of research (uncertain logic) "interesting" ... > > ben g > > On Sun, Oct 12, 2008 at 2:07 PM, Pei Wang <[EMAIL PROTECTED]> wrote: >> >> Abram: The parameter 'k' does not really depend on the future, because >> it makes no assumption about what will happen in that period of time. >> It is just a "ruler" or "weight" (used with scale) to measure the >> amount of evidence, as a "reference amount". >> >> For other people: The definition of confidence c = w/(w+k) states that >> confidence is the proportion of current evidence among future >> evidence, after the coming of evidence of amount k. >> >> Pei >> >> On Sun, Oct 12, 2008 at 1:48 PM, Abram Demski <[EMAIL PROTECTED]> >> wrote: >> > Pei, >> > >> > In this context, how do you justify the use of 'k'? It seems like, by >> > introducing 'k', you add a reliance on the truth of the future "after >> > k observations" into the semantics. Since the induction/abduction >> > formula is dependent on 'k', the truth values that result no longer >> > only summarize experience; they are calculated with prediction in >> > mind. >> > >> > --Abram >> > >> > On Sun, Oct 12, 2008 at 8:29 AM, Pei Wang <[EMAIL PROTECTED]> >> > wrote: >> >> A brief and non-technical description of the two types of semantics >> >> mentioned in the previous discussions: >> >> >> >> (1) Model-Theoretic Semantics (MTS) >> >> >> >> (1.1) There is a world existing independently outside the intelligent >> >> system (human or machine). >> >> >> >> (1.2) In principle, there is an objective description of the world, in >> >> terms of objects, their properties, and relations among them. >> >> >> >> (1.3) Within the intelligent system, its knowledge is an approximation >> >> of the objective description of the world. >> >> >> >> (1.4) The meaning of a symbol within the system is the object it >> >> refers to in the world. >> >> >> >> (1.5) The truth-value of a statement within the system measures how >> >> close it approximates the fact in the world. >> >> >> >> (2) Experience-Grounded Semantics (EGS) >> >> >> >> (2.1) There is a world existing independently outside the intelligent >> >> system (human or machine). [same as (1.1), but the agreement stops >> >> here] >> >> >> >> (2.2) Even in principle, there is no objective description of the >> >> world. What the system has is its experience, the history of its >> >> interaction of the world. >> >> >> >> (2.3) Within the intelligent system, its knowledge is a summary of its >> >> experience. >> >> >> >> (2.4) The meaning of a symbol within the system is determined by its >> >> role in the experience. >> >> >> >> (2.5) The truth-value of a statement within the system measures how >> >> close it summarizes the relevant part of the experience. >> >> >> >> To further simplify the description, in the context of learning and >> >> reasoning: MTS takes "objective truth" of statements and "real >> >> meaning" of terms as aim of approximation, while EGS refuses them, but >> >> takes experience (input data) as the only thing to depend on. >> >> >> >> As usual, each theory has its strength and limitation. The issue is >> >> which one is more proper for AGI. MTS has been dominating in math, >> >> logic, and computer science, and therefore is accepted by the majority >> >> people. Even so, it has been attacked by other people (not only the >> >> EGS believers) for many reasons. >> >> >> >> A while ago I made a figure to illustrate this difference, which is at >> >> http://nars.wang.googlepages.com/wang.semantics-figure.pdf . A >> >> manifesto of EGS is at >> >> http://nars.wang.googlepages.com/wang.semantics.pdf >> >> >> >> Since the debate on the nature of "truth" and "meaning" has existed >> >> for thousands of years, I don't think we can settle down it here by >> >> some email exchanges. I just want to let the interested people know >> >> the theoretical background of the related discussions. >> >> >> >> Pei >> >> >> >> >> >> On Sat, Oct 11, 2008 at 8:34 PM, Ben Goertzel <[EMAIL PROTECTED]> wrote: >> >>> >> >>> >> >>> >> >>> Hi, >> >>> >> >> > What this highlights for me is the idea that NARS truth values >> > attempt >> > to reflect the evidence so far, while probabilities attempt to >> > reflect >> > the world >> >>> >> >>> I agree that probabilities attempt to reflect the world >> >>> >> >> . >> >> Well said. This is exactly the difference between an >> experience-grounded semantics and a model-theoretic
Re: [agi] two types of semantics [Was: NARS and probability]
Pei, You are right, it doesn't make any such assumptions while Bayesian practice does. But, the parameter 'k' still fixes the length of time into the future that we are interested in predicting, right? So it seems to me that the truth value must be predictive, if its calculation depends on what we want to predict. That is why 'k' is hard to incorporate into the probabilistic NARSian scheme I want to formulate... --Abram On Sun, Oct 12, 2008 at 2:07 PM, Pei Wang <[EMAIL PROTECTED]> wrote: > Abram: The parameter 'k' does not really depend on the future, because > it makes no assumption about what will happen in that period of time. > It is just a "ruler" or "weight" (used with scale) to measure the > amount of evidence, as a "reference amount". > > For other people: The definition of confidence c = w/(w+k) states that > confidence is the proportion of current evidence among future > evidence, after the coming of evidence of amount k. > > Pei > > On Sun, Oct 12, 2008 at 1:48 PM, Abram Demski <[EMAIL PROTECTED]> wrote: >> Pei, >> >> In this context, how do you justify the use of 'k'? It seems like, by >> introducing 'k', you add a reliance on the truth of the future "after >> k observations" into the semantics. Since the induction/abduction >> formula is dependent on 'k', the truth values that result no longer >> only summarize experience; they are calculated with prediction in >> mind. >> >> --Abram >> >> On Sun, Oct 12, 2008 at 8:29 AM, Pei Wang <[EMAIL PROTECTED]> wrote: >>> A brief and non-technical description of the two types of semantics >>> mentioned in the previous discussions: >>> >>> (1) Model-Theoretic Semantics (MTS) >>> >>> (1.1) There is a world existing independently outside the intelligent >>> system (human or machine). >>> >>> (1.2) In principle, there is an objective description of the world, in >>> terms of objects, their properties, and relations among them. >>> >>> (1.3) Within the intelligent system, its knowledge is an approximation >>> of the objective description of the world. >>> >>> (1.4) The meaning of a symbol within the system is the object it >>> refers to in the world. >>> >>> (1.5) The truth-value of a statement within the system measures how >>> close it approximates the fact in the world. >>> >>> (2) Experience-Grounded Semantics (EGS) >>> >>> (2.1) There is a world existing independently outside the intelligent >>> system (human or machine). [same as (1.1), but the agreement stops >>> here] >>> >>> (2.2) Even in principle, there is no objective description of the >>> world. What the system has is its experience, the history of its >>> interaction of the world. >>> >>> (2.3) Within the intelligent system, its knowledge is a summary of its >>> experience. >>> >>> (2.4) The meaning of a symbol within the system is determined by its >>> role in the experience. >>> >>> (2.5) The truth-value of a statement within the system measures how >>> close it summarizes the relevant part of the experience. >>> >>> To further simplify the description, in the context of learning and >>> reasoning: MTS takes "objective truth" of statements and "real >>> meaning" of terms as aim of approximation, while EGS refuses them, but >>> takes experience (input data) as the only thing to depend on. >>> >>> As usual, each theory has its strength and limitation. The issue is >>> which one is more proper for AGI. MTS has been dominating in math, >>> logic, and computer science, and therefore is accepted by the majority >>> people. Even so, it has been attacked by other people (not only the >>> EGS believers) for many reasons. >>> >>> A while ago I made a figure to illustrate this difference, which is at >>> http://nars.wang.googlepages.com/wang.semantics-figure.pdf . A >>> manifesto of EGS is at >>> http://nars.wang.googlepages.com/wang.semantics.pdf >>> >>> Since the debate on the nature of "truth" and "meaning" has existed >>> for thousands of years, I don't think we can settle down it here by >>> some email exchanges. I just want to let the interested people know >>> the theoretical background of the related discussions. >>> >>> Pei >>> >>> >>> On Sat, Oct 11, 2008 at 8:34 PM, Ben Goertzel <[EMAIL PROTECTED]> wrote: Hi, > > > What this highlights for me is the idea that NARS truth values attempt > > to reflect the evidence so far, while probabilities attempt to reflect > > the world I agree that probabilities attempt to reflect the world > > . > > Well said. This is exactly the difference between an > experience-grounded semantics and a model-theoretic semantics. I don't agree with this distinction ... unless you are construing "model theoretic semantics" in a very restrictive way, which then does not apply to PLN. If by model-theoretic semantics you mean something like what Wikipedia says at http://en.wikipedia.org/wiki/Formal_semantics, *** Model-theoretic semantics i
Re: [agi] two types of semantics [Was: NARS and probability]
On Sun, Oct 12, 2008 at 3:06 PM, Abram Demski <[EMAIL PROTECTED]> wrote: > Pei, > > You are right, it doesn't make any such assumptions while Bayesian > practice does. But, the parameter 'k' still fixes the length of time > into the future that we are interested in predicting, right? So it > seems to me that the truth value must be predictive, if its > calculation depends on what we want to predict. The truth-value is defined/measured according to past experience, but is used to predict future experience. Especially, this is what the "expectation" function is about. But still, a high expectation only means that the system will behave under the assumption that the statement may be confirmed again, which by no means guarantee the actual confirmation of the statement in the future. > That is why 'k' is hard to incorporate into the probabilistic NARSian > scheme I want to formulate... For this purpose, the interval version of the truth value may be easier. Pei > --Abram > > On Sun, Oct 12, 2008 at 2:07 PM, Pei Wang <[EMAIL PROTECTED]> wrote: >> Abram: The parameter 'k' does not really depend on the future, because >> it makes no assumption about what will happen in that period of time. >> It is just a "ruler" or "weight" (used with scale) to measure the >> amount of evidence, as a "reference amount". >> >> For other people: The definition of confidence c = w/(w+k) states that >> confidence is the proportion of current evidence among future >> evidence, after the coming of evidence of amount k. >> >> Pei >> >> On Sun, Oct 12, 2008 at 1:48 PM, Abram Demski <[EMAIL PROTECTED]> wrote: >>> Pei, >>> >>> In this context, how do you justify the use of 'k'? It seems like, by >>> introducing 'k', you add a reliance on the truth of the future "after >>> k observations" into the semantics. Since the induction/abduction >>> formula is dependent on 'k', the truth values that result no longer >>> only summarize experience; they are calculated with prediction in >>> mind. >>> >>> --Abram >>> >>> On Sun, Oct 12, 2008 at 8:29 AM, Pei Wang <[EMAIL PROTECTED]> wrote: A brief and non-technical description of the two types of semantics mentioned in the previous discussions: (1) Model-Theoretic Semantics (MTS) (1.1) There is a world existing independently outside the intelligent system (human or machine). (1.2) In principle, there is an objective description of the world, in terms of objects, their properties, and relations among them. (1.3) Within the intelligent system, its knowledge is an approximation of the objective description of the world. (1.4) The meaning of a symbol within the system is the object it refers to in the world. (1.5) The truth-value of a statement within the system measures how close it approximates the fact in the world. (2) Experience-Grounded Semantics (EGS) (2.1) There is a world existing independently outside the intelligent system (human or machine). [same as (1.1), but the agreement stops here] (2.2) Even in principle, there is no objective description of the world. What the system has is its experience, the history of its interaction of the world. (2.3) Within the intelligent system, its knowledge is a summary of its experience. (2.4) The meaning of a symbol within the system is determined by its role in the experience. (2.5) The truth-value of a statement within the system measures how close it summarizes the relevant part of the experience. To further simplify the description, in the context of learning and reasoning: MTS takes "objective truth" of statements and "real meaning" of terms as aim of approximation, while EGS refuses them, but takes experience (input data) as the only thing to depend on. As usual, each theory has its strength and limitation. The issue is which one is more proper for AGI. MTS has been dominating in math, logic, and computer science, and therefore is accepted by the majority people. Even so, it has been attacked by other people (not only the EGS believers) for many reasons. A while ago I made a figure to illustrate this difference, which is at http://nars.wang.googlepages.com/wang.semantics-figure.pdf . A manifesto of EGS is at http://nars.wang.googlepages.com/wang.semantics.pdf Since the debate on the nature of "truth" and "meaning" has existed for thousands of years, I don't think we can settle down it here by some email exchanges. I just want to let the interested people know the theoretical background of the related discussions. Pei On Sat, Oct 11, 2008 at 8:34 PM, Ben Goertzel <[EMAIL PROTECTED]> wrote: > > > > Hi, > >> >> > What this highlights for me is the idea that NARS truth values attempt >> > to reflect the evi
[agi] Hugh Loebner talks AI
Hugh Loebner talks AI http://developers.slashdot.org/article.pl?sid=08/10/11/2137200 I may have written my signature twice on the OpenCog list, earlier today. I'm going to try to not do that. Otherwise I have nothing to report --- 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=8660244&id_secret=117534816-b15a34 Powered by Listbox: http://www.listbox.com
