dan@ADS.ARPA (Dan Shapiro) (11/11/87)
I am looking for someone who would be interested in discussing some ideas that involve both the fields of animal behavior and planning as a subdiscipline of AI. My goal is to develop a realistic view of what planning means to simple animals (at the level of ants for example) and use that information to motivate planning architectures within AI. Within this context, my focal point is to look at *errors* in animal behavior, as when ants build circular bridges out of their own bodies, and the ones on top simply run themselves to death. This should give a sense for the limitations of animal planning and also prevent us from anthropormorphizing to extremes; the temptation is to view behavior like the above as goal directed and related to our concept of "bridge building", when the presence of the error indicates that something much more primitive is going on. From the little I have seen of literature in the behavioral sciences, this type of projection is fairly common. In any case, as a first step, I'd like to gather multiple examples of errors in animal behavior. If there are any ethologists, sociobiologists, neuroanatomists, computer scientists or just plain armchair behaviorists out there who have something to say on this topic, please contact me. Dan Shapiro dan@ads.com 415 941-3912
mps@CS.DUKE.EDU (Michael P. Smith) (11/14/87)
In article <8711110303.AA28544@ADS.ARPA> dan@ADS.ARPA (Dan Shapiro) writes: > ... My goal is to develop a realistic view of what >planning means to simple animals (at the level of ants for example) >and use that information to motivate planning architectures within AI. >Within this context, my focal point is to look at *errors* in animal >behavior, as when ants build circular bridges out of their own bodies, >and the ones on top simply run themselves to death. Hofstadter calls such revealing lapses of animal cunning "sphexishness" after a famous example from Wooldridge. Chapter 2 of Dennett provides more philosophical analysis of the phenomenon. Dennett, Daniel C. _Elbow Room_, MIT 1984. Hofstadter, Douglas. "On the Seeming Paradox of Mechanizing Creativity," _Scientific American_ (September 1982), reprinted as chapter 23 of _Metamagical Themas_, Basic Books, 1985. Wooldridge, Dean. _The Machinery of the Brain_, McGraw Hill, 1963. ---------------------------------------------------------------------------- Michael P. Smith mps@cs.duke.edu / {seismo,decvax}!mcnc!duke!mps "V. That which a lover takes against the will of his beloved has no relish." Andreas Capellanus' "Rules of Love" from _The Art of Courtly Love_ ----------------------------------------------------------------------------
dan@ADS.COM (Dan Shapiro) (08/25/88)
To: ames!comp-ai-digest@ames.arc.nasa.gov Path: zodiac!dan From: Dan Shapiro <zodiac!ads.com!dan@ames.arc.nasa.gov> Newsgroups: comp.ai.digest Subject: Animal Behavior and AI Date: Mon, 22 Aug 88 14:42 EDT References: <19880820041306.5.NICK@HOWARD-JOHNSONS.LCS.MIT.EDU> Sender: zodiac!ads.com!news@ames.arc.nasa.gov Reply-To: Dan Shapiro <zodiac!ads.com!dan@ames.arc.nasa.gov> Organization: Advanced Decision Systems, Mt. View, CA (415) 960-7300 Lines: 18 Motion control isn't the only area where studying animals has merit. I have been toying with the idea of studying planning behavior in various creatures; a reality check would add to the current debate about "logical forethought" vs. "reactive execution" in the absence of plan structures. A wrinkle is that it would be very hard to get a positive fix on an animal's planning capabilities since all we can observe is their behavior (which could be motivated by a range of mechanisms). My thought is to study what we would call "errors" in animal behavior - behaviors that a more cognizant or capable planning engine would avoid. It seems to me that there must be a powerful difference between animal planning/action strategies and (almost all) current robotic approaches; creatures manage to do something reasonable (they survive) in a wide variety of situations while robots require very elaborate knowledge in order to act in narrow domains.