Although I thought this was a good talk and I liked the fellow presenting it to me it seems fairly clear that little or no progress has been made in this area over the last decade or so. In the early 1990s I wrote somewhat similar simulations where agents had their own neural networks whose architecture was specified by a genetic algorithm, but just like the speaker I came up against similar problems.
As the guy says it should be in principle possible to "go all the way" from simple types of creatures up to more complex ones, like humans. In practice though what tends to happen is that the complexity of the neural nets reaches a plateau from which little subsequent progress occurs. Even after allowing the system to run for tens of thousands of generations not much of interest happens. I think the main problem here is the low complexity of the environment and the agents themselves. In a real biological system there are all kinds of niches which can be exploited in a variety of ways, but in polyworld (and other similar simulations) it's all very homogeneous. Real biological creatures are coalitions of millions of cells, each of which is a chemical factory containing an abundance of nano machinery, each of which is a possible site for evolutionary change. The sensory systems of real creatures are also far richer than simply being able to detect three colours (even molluscs can do better than this), and this is obviously a limiting factor upon the development of greater intelligence. On 15/11/2007, Jef Allbright <[EMAIL PROTECTED]> wrote: > This may be of interest to the group. > > <http://video.google.com/videoplay?docid=-112735133685472483> > > > This presentation is about a potential shortcut to artificial > intelligence by trading mind-design for world-design using artificial > evolution. Evolutionary algorithms are a pump for turning CPU cycles > into brain designs. With exponentially increasing CPU cycles while our > understanding of intelligence is almost a flat-line, the evolutionary > route to AI is a centerpiece of most Kurzweilian singularity > scenarios. This talk introduces the Polyworld artificial life > simulator as well as results from our ongoing attempt to evolve > artificial intelligence and further the Singularity. > > Polyworld is the brain child of Apple Computer Distinguished Scientist > Larry Yaeger, who remains the primary developer of Polyworld: > > http://www.beanblossom.in.us/larryy/P... > > Speaker: Virgil Griffith > Virgil Griffith is a first year graduate student in Computation and > Neural Systems at the California Institute of Technology. On weekdays > he studies evolution, computational neuroscience, and artificial life. > He did computer security work until his first year of university when > his work got him sued for sedition and espionage. He then decided that > security was probably not safest field to be in and he turned his life > to science. (less) > Added: November 13, 2007 > > - Jef > > ----- > 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=8660244&id_secret=65298881-4c0739
