I may be coming in from left field and haven't read a lot of these discussions on defining intelligence, but defining intelligence verbally, yes, it can have numerous descriptions and arguments. But I need something concrete and measurable in the form of an equation. Is that too much to ask for? I mean that's how it usually works right?
Intelligence - we're talking about storing and flipping bits - minimalistically that's it. How many variables will it take to come up with an equation? 6? 7? Some of the variables are specific and some may be general. One may be a measurement of complexity, one a vector set including a generalized description of goals?, I don't know...another a KR? Either way there are just a few variables going on here and someone needs to propose a few candidate equations for review. Perhaps there are some in previous posts that I missed or do I need to come up with something myself :). John > -----Original Message----- > From: Pei Wang [mailto:[EMAIL PROTECTED] > Sent: Wednesday, May 16, 2007 11:22 AM > To: agi@v2.listbox.com > Subject: Re: [agi] definitions of intelligence, again?! > > On 5/16/07, Shane Legg <[EMAIL PROTECTED]> wrote: > > > > > No. To me that is not intelligence, though it works even better. > > > > This seems to me to be very divergent from the usual meaning > > of the word intelligence. It opens up the possibility that a super > > computer that is able to win a Nobel prize by running a somewhat > > efficient AI algorithm could be less intelligent than a basic pocket > > calculator that is solving optimization problems in a very efficient > way. > > This just shows the complexity of "the usual meaning of the word > intelligence" --- many people do associate with the ability of solving > hard problems, but at the same time, many people (often the same > people!) don't think a brute-force solution show any intelligence. > When "intelligence" is used on human, there is no problem, since few > hard problem can be solved by the human mind by brute-force. However, > when we extend this notion to cover computers, we cannot keep both, > since their consistent is no longer guaranteed (as shown by your > example). At this point, you see "capability" as more essential, while > I see "adaptivity" as more essential. > > There is no objective or truer answer, though we should understand > what we've given up. In my side, I admit that an intelligent system > doesn't always provide a batter solution than a non-intelligent one, > and I don't see it as a problem --- today, conventional computers > solve many problems better than the human mind, but I don't take that > as reason for them to be more intelligent. > > In this discussion, I have no intention to convince people that my > definition of intelligence is better --- for most people, that will > happen only when my system is producing results that they consider as > impressive, which will not happen soon. Instead, I want to argue that > at the current moment there are multiple notions of intelligence, > which are all justifiable to various degrees. However they are not > equivalent, since they lead the research to different directions. > > To me, on this topic the current danger is not that we have different > understandings on what intelligence is (this is undesired, though > inevitable at the current stage), but that there are still many people > who believe that "intelligence" only has one true/correct > understanding, which is how they understand it. > > > It seems to me that what you are defining would be better termed > > "intelligence efficiency" rather than "intelligence". > > What if I suggest to rename your notion "universal problem solver"? ;-) > > > > They don't need to have the test in mind, indeed, but how can you > > > justify the authority and fairness of the testing results, if many > > > systems are not built to achieve what you measure? > > > > I don't see that as a problem. By construction universal intelligence > > measures how well a system is able to act as an extremely general > > purpose problem solver (roughly stated). This is what I would like to > > have, and so universal intelligence is a good measure of what I am > > interested in achieving. I happen to believe that this is also a > decent > > formalisation of the meaning of "intelligence" for machines. Some > > systems might be very good at what they have been designed to do, > > but what I want to know is how good are they as a general purpose > > problem solver? If I can't give them a problem, by defining a goal > > for them, and have them come up with a very clever solution to my > > problem, they aren't what I'm interested in with my AI work. > > This is exactly the problem I mentioned above. What if I don't think > "universal intelligence" means "general-purpose problem solver" as you > define it? Of course, if I'm the only one, you don't need to worry, > but I really don't see how you can put the current AGI projects, which > are as diverse one can image, into the framework you are proposing. If > you simply say that the one that don't fit in are uninteresting to > you, the others can say the same to your framework, right? For > example, I'm not interested in brute-force solutions, even though I > know some day some of them may solve Nobel-Prize-level problems. I > agree that kind of solution has huge practical potentials, and I value > other people's work on that direction. I just doing think it is AI, > and its success won't solve the problem I'm interested in. > > In summary, I highly appreciate your attempt to unify the field by > building a common evaluation framework, but I hope to show that your > understanding/specification of the problem is not the only possible > one at the current moment. > > Pei > > ----- > This list is sponsored by AGIRI: http://www.agiri.org/email > To unsubscribe or change your options, please go to: > http://v2.listbox.com/member/?&; ----- This list is sponsored by AGIRI: http://www.agiri.org/email To unsubscribe or change your options, please go to: http://v2.listbox.com/member/?member_id=231415&user_secret=fabd7936
