RE: [agi] Thinking may be overrated.
Kevin Copple wrote: > I do not want to say that random trial and error is the ultimate form of > intelligent thought. Far from it. But given what nature and > humankind have > achieved with it to date, and that we may not even recognize the extent to > which it is involved in our own thought, it seems to be an intriguing > ingredient. Perhaps artificial trial and error systems can lead > us to "pure > intelligence." That is, if pure intelligence is not an illusion, > a mirage, > an unachievable holy grail. Well, I agree with you that "random trial and error" is an "intriguing ingredient" and an important ingredient of cognition. Evolutionary programming is a key aspect of Novamente's "procedure learning" module, which is one of Novamente's most important components. But regarding "artificial trial and error can lead us to pure intelligence" -- I think it can, but only after a long time. I don't think this is anywhere near the shortest path... I don't think a mind based primarily on "trial and error" could run on viable hardware. I think that a digital evolution process based on trial and error could lead to the evolution of a mind, but this would take a while !! -- Ben --- To unsubscribe, change your address, or temporarily deactivate your subscription, please go to http://v2.listbox.com/member/?[EMAIL PROTECTED]
RE: [agi] Thinking may be overrated.
Hi Kevin, "Trial and error" describes an approach to learning, and I think the issue you are getting at is that thinking (i.e., reasoning and planning) must be grounded in learning, in the same way that symbols must be grounded in sensory experience. This can be understood in terms of the general steps of brain evolution: 1. sensors -> nerve cells -> actions 2. reinforcement learning of behaviors in response to sensory stimuli, including the beginnings of reinforcement values such as "eating is good" 3. simulation (i.e., brains processing experiences that are not actually occuring) in order to begin solving the temporal credit assignment problem (this is the problem of reinforcing behaviors when rewards occur significantly later than behaviors, and multiple behaviors occur before rewards) 4. increasingly sophisticated simulation (planning, simulating brains of other animals) and values (social values for teamwork) To see how planning fits into learning, consider that when humans confront novel situations they consciously plan their behaviors, based on simulated scenarios. As they repeat the situation and it is less novel, those planned behaviors become unconscious. Furthermore, those unconscious behaviors become part of the repitoire for future planning. This relation between planning and learning is illustrated by the development of a beginning chess player into a chess master. A beginner's plans may include as many alternatives as a master's, but the master's plans are in terms of a repitoire of behaviors learned through lots of previous plans and reinforcement. Note that this analysis is different from Skinner's behaviorism because it deals with the way an internal mental life (i.e., simulation) fits into the learning of behaviors. Cheers, Bill -- Bill Hibbard, SSEC, 1225 W. Dayton St., Madison, WI 53706 [EMAIL PROTECTED] 608-263-4427 fax: 608-263-6738 http://www.ssec.wisc.edu/~billh/vis.html On Mon, 30 Dec 2002, Kevin Copple wrote: > Ben Goertzel wrote: > > Traditional logic-based AI has badly underemphasized the role of trial and > >error, but I'm afraid you're swinging to the opposite extreme !! > > It has been said that it is easier to bring a wild idea under control than > to give life into a lame idea, so considering an extreme position may not be > a bad tactic. > > In further defense of trial and error, I would point out that much or most > of our human knowledge and progress has been the result of countless random > trials and errors of others. If the pre-Columbian Native Americans had a > strong value for seeking advancement through trial and error, I imagine they > would have discovered much better archery techniques that would have > dramatically altered human history. Would those countless archers have met > the criteria for AGI? Surely they would have. But they apparently lacked > respect for random trial and error in the pursuit of progress. Clearly they > WANTED their arrows to have three times the range, speed and power. Seems > this is an obvious case of an AGI (minus the "artificial") that desperately > needed the random trial and error problem solving method. > > In my life, I have found that various forms of negative feedback often > taught me an effective lesson, even though I intellectually KNEW the lesson > beforehand. As in, "I knew that was a bad idea, tried it anyway, and will > never again." I have seen this behavior many times in others as well. This > is the type of observation that makes me wonder the extent to which emotion > is the real driver in our intelligent behavior. WANTING to succeed often > seems to be the real factor in success at solving problems. > > What is the pattern matching that occurs in our biological neural nets? Is > it not a simple "trial and error," with more dimensions? To me, seeing a > pattern in a series of words, images, or numbers in an IQ test is a type of > trial and error. I am getting beyond my ability to express myself, at > least without more energy and time than I have at the moment, but it occurs > to me that what we perceive as logic in our brains is actually massively > parallel trial and error processes with emotional reinforcement for success > or failure. > > I do not want to say that random trial and error is the ultimate form of > intelligent thought. Far from it. But given what nature and humankind have > achieved with it to date, and that we may not even recognize the extent to > which it is involved in our own thought, it seems to be an intriguing > ingredient. Perhaps artificial trial and error systems can lead us to "pure > intelligence." That is, if pure intelligence is not an illusion, a mirage, > an unachievable holy grail. > > Cheers, > > Kevin Copple > > --- > To unsubscribe, change your address, or temporarily deactivate your subscription, > please go to http://v2.listbox.com/member/?[EMAIL PROTECTED
RE: [agi] Thinking may be overrated.
Ben Goertzel wrote: > Traditional logic-based AI has badly underemphasized the role of trial and >error, but I'm afraid you're swinging to the opposite extreme !! It has been said that it is easier to bring a wild idea under control than to give life into a lame idea, so considering an extreme position may not be a bad tactic. In further defense of trial and error, I would point out that much or most of our human knowledge and progress has been the result of countless random trials and errors of others. If the pre-Columbian Native Americans had a strong value for seeking advancement through trial and error, I imagine they would have discovered much better archery techniques that would have dramatically altered human history. Would those countless archers have met the criteria for AGI? Surely they would have. But they apparently lacked respect for random trial and error in the pursuit of progress. Clearly they WANTED their arrows to have three times the range, speed and power. Seems this is an obvious case of an AGI (minus the "artificial") that desperately needed the random trial and error problem solving method. In my life, I have found that various forms of negative feedback often taught me an effective lesson, even though I intellectually KNEW the lesson beforehand. As in, "I knew that was a bad idea, tried it anyway, and will never again." I have seen this behavior many times in others as well. This is the type of observation that makes me wonder the extent to which emotion is the real driver in our intelligent behavior. WANTING to succeed often seems to be the real factor in success at solving problems. What is the pattern matching that occurs in our biological neural nets? Is it not a simple "trial and error," with more dimensions? To me, seeing a pattern in a series of words, images, or numbers in an IQ test is a type of trial and error. I am getting beyond my ability to express myself, at least without more energy and time than I have at the moment, but it occurs to me that what we perceive as logic in our brains is actually massively parallel trial and error processes with emotional reinforcement for success or failure. I do not want to say that random trial and error is the ultimate form of intelligent thought. Far from it. But given what nature and humankind have achieved with it to date, and that we may not even recognize the extent to which it is involved in our own thought, it seems to be an intriguing ingredient. Perhaps artificial trial and error systems can lead us to "pure intelligence." That is, if pure intelligence is not an illusion, a mirage, an unachievable holy grail. Cheers, Kevin Copple --- To unsubscribe, change your address, or temporarily deactivate your subscription, please go to http://v2.listbox.com/member/?[EMAIL PROTECTED]
RE: [agi] Thinking may be overrated.
Kevin Copple wrote: > "Thinking" in humans, much like genetic evolution, seems to involve > predominately trial and error. Even the "logic" we like to use is more > often than not faulty, but can lead us to try something different. And > example of popular logic that is invariably faulty is reasoning > by analogy. > It is attractive, but always breaks down on close examination. But this > type of reasoning will lead to a trial that may succeed, possibly > because of > the attractive similarities, but more likely in spite of them. I don't agree with this paragraph, although I see some truth in it. I think that "trial and error" based idea-evolution is one important aspect of human cognition, but not the *predominant* aspect. It may predominate in some circumstances, but these would be unusual ones where there was little pertinent background knowledge Analogical inference can be formulated rigorously in probabilistic terms. It does have a "guesswork" aspect to it, but it's a well-organized way of managing conditional probabilities... in my view ;_) In Novamente, we have an EvolutionaryConceptCreation MindAgent which explicitly uses trial and error to create new ideas. But it is intended for use together with other MindAGents, including those implementing probabilistic inference If you set the parameters of the system so that evolutionary concept creation predominated, I think you'd find a system with far below optimal functionality.. Traditional logic-based AI has badly underemphasized the role of trial and error, but I'm afraid you're swinging to the opposite extreme !! -- Ben --- To unsubscribe, change your address, or temporarily deactivate your subscription, please go to http://v2.listbox.com/member/?[EMAIL PROTECTED]
