HDTenEightyP/NetNews huggingface dataset:
From: kv07@IASTATE.EDU (Warren Vonroeschlaub)
Subject: Re: Simple problems to solve genetically
Reply-To: kv07@IASTATE.EDU (Warren Vonroeschlaub)
Organization: Ministry of Silly Walks
Date: Tue, 12 Jan 1993 18:05:25 GMT

In article <7268265448-38850@exaia>, bruhn@exaia (Peter Bruhn ) writes:
>In article <1993Jan11.145224@IASTATE.EDU> from [Mon, 11 Jan 1993 20:52:24 GMT]
you wrote:
>> In article <1993Jan8.202702.21180@fcom.cc.utah.edu>,
>> freier@mail.physics.utah.edu (rodney james freier) writes:
>> >   I'm looking for a few simple games/problems that can be played/solved
>> > genetically.  I'm just trying to practice with the concept.
>> 
>>   Just about any game with an evaluation phase can be done (chess, checkers,
>> tic-tac-toe).  Just have an alpha-beta search with node rating, and evolve
>> different ways to rate nodes.  I did this way back with connect-four.
>> 
>>   I think some of the top chess programs already do this.
> 
>Really? I am highly interested in more information. What chess program does
>use GAs? Any references?

  I remember hearing that Carnegie Mellon's "Deep Thought" chess player had its
position evaluater made by a GA (It was #1 in '90 or therabouts).  Can't give
any references though, sorry.  Try looking in the procedings of the computer
chess competitions at around that time.  Some others have done this too from
what I've heard.

 |  __L__
-|-  ___  Warren Kurt vonRoeschlaub
 |  | o | kv07@iastate.edu
 |/ `---' Iowa State University
/|   ___  Math Department
 |  |___| 400 Carver Hall
 |  |___| Ames, IA  50011
 J  _____
From: rice@sumex-aim.Stanford.EDU (James Rice)
Newsgroups: comp.ai.genetic
Subject: Re: Anyone know of a good intro paper/book?
Date: 12 Jan 93 08:52:52
Organization: Knowledge Systems Lab, Stanford University
NNTP-Posting-Host: hpp-ipc-2.stanford.edu
In-reply-to: kcj@vulcan.anu.edu.au's message of 12 Jan 1993 02:26:47 GMT


I seem to recall that Larry Davis has also done a series of
lecture/movies.  I don't remember who publishes them, but I
remember they had a booth at AAAI and were also selling a
bunch of tapes on fuzzy systems.  If you have enough $s
then they may be a good way to get into the field.  I think
they may be a little pricey (for the normal human) but are
likely to be very cheap relative to the man hours spent
figuring out how to learn about GAs.

Of course (yawn), JK's book is the right intro to GP, but it
sounds like you're more interested in straight GAs.

Goldberg's book is probably worth looking at.  I don't remember
whether it has been mentioned.

  Genetic Algorithms in Search, Optimisation and Machine Learning
  Goldberg, David E. 1989, Addison-Wesley.

I haven't read Holand's book, but I gather that it is absolutely
NOT the right place to start.


Rice.
Newsgroups: comp.ai.genetic
From: lains@world.std.com (Layne L Ainsworth)
Subject: Re: Simple problems to solve genetically
Organization: The World
Date: Sat, 9 Jan 1993 00:07:31 GMT


On the BlackJack problem:

aIt might be knd of interesting to give as input the history of all
cards turned up in the game (current shoe). Emergent card counting!

Just a notion.

-- 
  Layne Ainsworth | lains@world.std.com <or> ...!{xylogics,uunet}!world!lains
	  The truth can't hurt you; it's just like the dark.

Newsgroups: comp.ai.genetic
From: sonny@charybdis.harris-atd.com (Bob Davis)
Subject: Re: Anyone know of a good intro paper/book?
Date: Tue, 12 Jan 1993 15:29:08 GMT
Reply-To: sonny@trantor.harris-atd.com (Bob Davis)
Organization: Advanced Technology Dept., Harris ESS, Melbourne, FL

In article <1ita97INN5n5@manuel.anu.edu.au> kcj@vulcan.anu.edu.au (Kate Juliff) writes:
>In article <JET.93Jan11144017@boxer.nas.nasa.gov> jet@boxer.nas.nasa.gov (J. Eric Townsend) writes:
>>
>>Anybody have a suggestion for a good introductory paper or book?  I've
	[DELETIONS]
>Also worth reading is the article on GAs in the Sept 93
> _Scientific_American_.                         
                                                 ^^^^^^^
						This, of course, was
the highly-regarded issue on "NON-CAUSAL PHENOMENA." :-)


_____________________________________________________________________________
Bob Davis, UofALA alum \\ INTERNET: sonny@trantor.harris-atd.com  |  _   _  |
Harris Corporation, ESS \\    UUCP: ...!uunet!x102a!trantor!sonny |_| |_| | |
Advanced Technology Dept.\\ AETHER: K4VNO          |==============|_/\/\/\|_|
PO Box 37, MS 16/1912     \\ VOICE: (407) 727-5886 | I SPEAK ONLY | |_| |_| |
Melbourne, FL 32902 USA    \\  FAX: (407) 729-3363 | FOR MYSELF.  |_________|

Newsgroups: comp.ai.genetic
From: timm@spectrum.cs.unsw.oz.au (Tim Menzies)
Subject: wanted: 10 good articles...
Reply-To: timm@spectrum.cs.unsw.oz.au (Tim Menzies)
Organization: none
Date: Sun, 10 Jan 1993 06:45:47 GMT

i co-ordicate a reading group at my lab. there is some interest in doing
some ga work. what are N articles (N <= 10) that review the field, or
(whe they were published) set the field afire? 

#include standard-statement-re-post-summary

ADVthankANCE

--
 ,-_|\     Tim Menzies (timm@cs.unsw.oz.au)        | Small, dark, noisy room
/     \    AI Lab, Computer Science, Uni. NSW      | for rent. Get a haircut/
\_,-._* <- P.O. Box 1, Kensington, Australia, 2033 | job/ a life, then apply.
     v     +61-2-663-4576 (fax) +61-2-697-3940 (w) |  -- ad, Venice Beach, LA
From: mdlm@great-grain.ai.mit.edu (Michael De-la-Maza)
Newsgroups: comp.ai.genetic
Subject: Tournament selection
Date: 11 Jan 93 18:06:51 GMT
Organization: MIT Artificial Intelligence Lab
NNTP-Posting-Host: great-grain.ai.mit.edu

Lots of books (e.g., Goldberg's textbook and Koza's Genetic Programming)
refer to tournament selection.  However, I have been unable to find the
original source of the method.  Does anyone know what the original
citation is?
From: freier@mail.physics.utah.edu (rodney james freier)
Newsgroups: comp.ai.genetic
Subject: Re: Simple problems to solve genetically
Date: 11 Jan 93 23:15:50 GMT
Organization: University of Utah - Physics Department

In article <1993Jan11.145224@IASTATE.EDU>, kv07@IASTATE.EDU (Warren Vonroeschlaub) writes:
|>|> 
|>   I tried this when I first thought of genetic algorithm games.  The problem is
|> that it has already been thouroughly mapped out, so at best you could only match
|> what is already known :-(
|> 
|>
  Oh, that's ok.  I just wanted homework-type problems,  not senior project
problems.  I'm not looking to do any ground-breaking research.

Rod
From: kaveh@CAM.ORG (Kaveh Kardan)
Newsgroups: comp.ai.genetic
Subject: Source for Koza's book available via ftp?
Date: 9 Jan 93 20:50:38 GMT
Organization: Communications Accessibles Montreal, Quebec Canada


Is the source code from John Koza's book _Genetic Programming_ available
via ftp?

Thanks,

Kaveh

--
Kaveh Kardan                                        kaveh@mtrpls.login.qc.ca
Metropolis Graphics Ltd
Montreal Quebec Canada                              phone/fax: (514)842-6172

-- 
Kaveh Kardan                                        kaveh@mtrpls.login.qc.ca
Metropolis Graphics Ltd
Montreal Quebec Canada                              phone/fax: (514)842-6172
Newsgroups: comp.ai.genetic
From: lains@world.std.com (Layne L Ainsworth)
Subject: Use of Genetic Algorithms to evolve robot behavior?
Organization: The World @ Software Tool & Die
Date: Thu, 7 Jan 1993 23:45:35 GMT



Has anyone tried to do this: 

"Herds" of cheap (really cheap), reprogrammable robots, each loaded
with one set of the test "chromosome" population of a Genetic
Algorithm system. They could be evaluated to optimize indivdual
performance, or "hive" well-being.  Each "generation" would be the
same robots, with a new generation of "chromosomes" on board.

Pointers to papers or discussion of the feasibility of such a project
would both be welcome. I would think this could be a job for the
much-heralded and -scorned MiniBoard. Wire up all the connections to
various sensors/actuators and let the herd discover uses for them.

My dream, of course, is a bunch of robots that (who?) could
continuously clean my house. :-)

Thanks.

-Layne



-- 
  Layne Ainsworth | lains@world.std.com <or> ...!{xylogics,uunet}!world!lains
	  The truth can't hurt you; it's just like the dark.

Newsgroups: comp.ai.genetic
From: herman@nosc.mil (John W. Herman)
Subject: Re: Simple problems to solve genetically
Organization: Naval Ocean Systems Center, San Diego, CA
Date: Mon, 11 Jan 1993 21:30:00 GMT

kv07@IASTATE.EDU (Warren Vonroeschlaub) writes:

>In article <1993Jan8.202702.21180@fcom.cc.utah.edu>,
>freier@mail.physics.utah.edu (rodney james freier) writes:
*** Stuff deleted ***
>>  The best
>> simple project I've been able to come up with so far is generating a
>> Blackjack strategy genetically.

>  I tried this when I first thought of genetic algorithm games.  The problem is
>that it has already been thouroughly mapped out, so at best you could only match
>what is already known :-(

There are many variations of blackjack.  Such as one which used to be
played in the Las Vegas Club which allowed the player to buy back half of
his bet before he drew any cards.  A friend of mine James D. Pugh,
figured out a simple strategy where the player could (barely) have an
edge on the house.  An advantage of around 0.1%.  He has since died and
his strategy with him.  Seems to me that this idea could be the basis
for a GA.
Newsgroups: comp.ai.genetic
From: grey@bnr.ca (Bryan Miller)
Subject: Re: LISP
Reply-To: grey@bnr.ca (Bryan Miller)
Organization: Bell-Northern Research Ltd.
Date: Tue, 12 Jan 1993 18:28:45 GMT

In article <1993Jan12.153838.7079@ncsu.edu>, naoursla@eos.ncsu.edu
(NORMAN ALAN OURSLAND) writes:
 
> Hi. Does anyone know of a public domain LISP interpreter for UNIX, X-windows,
> or MS-DOS to use for playing around with GA? Thank you.

GNU's e-lisp works fine, and you get all the text-handling stuff as a bonus

-- 
------------------------------------------------------------------------------
grey@bnr.ca			              I think I know enough of hate
greymouser			     	      To say that for destruction ice
my own opinions, not those of my employer     Is also great, and would suffice
------------------------------------------------------------------------------
From: rice@sumex-aim.Stanford.EDU (James Rice)
Newsgroups: comp.ai.genetic
Subject: Re: 2-D Chromosomes
Date: 12 Jan 93 12:41:00
Organization: Knowledge Systems Lab, Stanford University
NNTP-Posting-Host: hpp-ipc-2.stanford.edu
In-reply-to: David.Beasley@cm.cf.ac.uk's message of 12 Jan 93 18:53:32 GMT

In article <1993Jan12.185333.20195@cm.cf.ac.uk> David.Beasley@cm.cf.ac.uk (David Beasley) writes:
   Does anyone know of any published GA work which has used 2-dimensional
   chromosomes?

   I've read significant proportions of all four ICGA proceedings, but
   didn't notice anything on this.
   --

Do you mean 2-dimensional in the sense of simply non-linear (for which
GP's tree structures are a good example) or specifically a kind of
rectangular character "string"?

If it's the latter, I'm not sure how this would be different
from a simple character string, since you can always
linearise a k-dimensional array.  The interpretation of the
coding scheme might change.  Mind you, sounds like the sort of
thing that someone would have done.



Rice.
From: David.Beasley@cm.cf.ac.uk (David Beasley)
Newsgroups: comp.ai.genetic
Subject: 2-D Chromosomes
Summary: References wanted
Date: 12 Jan 93 18:53:32 GMT
Organization: University of Wales College of Cardiff


Does anyone know of any published GA work which has used 2-dimensional
chromosomes?

I've read significant proportions of all four ICGA proceedings, but
didn't notice anything on this.
--

David Beasley                          (David.Beasley@cm.cf.ac.uk)    
Department of Computing Mathematics 
University of Wales College of Cardiff                          __o
PO Box 916                                                      \<,   
CARDIFF    CF2 4YN                         ___________________()/ ()___  
Newsgroups: comp.ai.genetic
From: kcj@vulcan.anu.edu.au (Kate Juliff)
Newsgroups: comp.ai.genetic
Subject: Re: Anyone know of a good intro paper/book?
Date: 12 Jan 1993 02:26:47 GMT
Organization: Australian National University, Canberra, Australia
NNTP-Posting-Host: 150.203.20.13

In article <JET.93Jan11144017@boxer.nas.nasa.gov> jet@boxer.nas.nasa.gov (J. Eric Townsend) writes:
>
>Anybody have a suggestion for a good introductory paper or book?  I've
>seen a few interesting papers, but they assume one is already *very*
>familiar with the thy and terminology involved.
>
I highly recommend _Handbook_of_Genetic_Algorithms_ Davis, L. (ed)
Van Nostrand Reinhold 1991.

It starts with a tutorial introduction and covers a range
of GAs inc order based GAs. It also has a number of interesting
papers.

Also worth reading is the article on GAs in the Sept 93
 _Scientific_American_.

--Kate

-- 
Kate Juliff                           | kcj@matilda.vut.edu.au
Victoria University                   |
P.O. BOX 14428,                       |
MELBOURNE MAIL CENTRE, AUSTRALIA 3000 |
From: tackett@ipld00.hac.com (Walter Alden Tackett)
Newsgroups: comp.ai.genetic
Subject: Re: Use of Genetic Algorithms to evolve robot behavior?
Date: 9 Jan 93 00:00:29 GMT
Organization: Hughes Aircraft Company - Canoga Park, CA

One more addendum to this topic: if you are interested in evolving the behavior
of single robots, I received a couple of papers from the U. of Sussex at
Brighton related to this topic.  As far as I know they are internal tech
reports:

``Issues in Evolutionary Robotics,'' I. Harvey, P. Husbands, and D. Cliff
CSRP #219, July 1992

``Evolving Visually Guided Robots,'' D. Cliff, P. Husbands, and I. Harvey
CSRP #220, July 1992

Authors may be contacted at: davec philh and inmanh @cogs.susx.ac.uk

-walter alden tackett

`` If we do not succeed, then we run the risk of failure. ''
			- (almost former) U.S.V.P. Dan Quayle
From: David.Beasley@cm.cf.ac.uk (David Beasley)
Newsgroups: comp.ai.genetic
Subject: Re: Tournament selection
Summary: Original Source
Date: 12 Jan 93 18:49:00 GMT
Organization: University of Wales College of Cardiff

In article <1iscvrINNcp2@life.ai.mit.edu> mdlm@great-grain.ai.mit.edu (Michael De-la-Maza) writes:
>Lots of books (e.g., Goldberg's textbook and Koza's Genetic Programming)
>refer to tournament selection.  However, I have been unable to find the
>original source of the method.  Does anyone know what the original
>citation is?

According to Goldberg & Deb [1] "A form of tournament selection
attributed to unpublished work by Wetzel was studied in Brindle's
(1981) [2] dissertation..."

So it looks like the original source was: (a) before 1981, and 
(b) unpublished.


[1] Goldberg & Deb (1990) "A Comparative analysis of selection schemes
used in genetic algorithms" TCGA report No. 90007, also published in
FOGA-91, ed. G.J. Rawlins.

[2] Brindle, A (1981) "Genetic algorithms for function optimisation"
(Doctoral dissertation, Univ. of Michigan). Dissertation abstracts
international, 36(10), 5140B (University Microfilms No. 76-9381)

--

David Beasley                          (David.Beasley@cm.cf.ac.uk)    
Department of Computing Mathematics 
University of Wales College of Cardiff                          __o
PO Box 916                                                      \<,   
CARDIFF    CF2 4YN                         ___________________()/ ()___  
Newsgroups: comp.ai.genetic
From: btarbox@world.std.com (Brian J Tarbox)
Subject: Re: Use of Genetic Algorithms to evolve robot behavior?
Organization: The World Public Access UNIX, Brookline, MA
Date: Fri, 8 Jan 1993 02:28:52 GMT

This is only sort-of related to GAs for robot behavior but I did
a masters' thesis on using GAs in a prolog system that attempted
to emulate the language learning abilities of bottlenosed dolphins.
We trained the simulation in the morning and trained the real dolphinsj
in the afternoon.  We tried to get the simulation to predict what sort
of things the real dolphins might do.

Brian Tarbox
Been There - Done That Software
From: tomf@gte.com (Tom Fawcett)
Newsgroups: comp.ai.genetic
Subject: Re: Simple problems to solve genetically
Date: 10 Jan 93 14:37:13 GMT
	<1993Jan9.192644.24693@fcom.cc.utah.edu>
	<1993Jan10.054202.9817@ils.nwu.edu>
Reply-To: tomf@gte.com
Organization: GTE Laboratories, Inc.
In-reply-to: mccoy@ils.nwu.edu's message of 10 Jan 93 05:42:02 GMT


I'm surprised by this discussion of how to represent blackjack so a
genetic algorithm could solve it.  If you have to put that much effort into
getting the representation just right, it seems like you -- the humans -- have
already done the interesting learning.

(Equivalently, maybe the problem isn't simple.)

-Tom
Newsgroups: comp.ai.genetic
From: toma@hyperion.gsfc.nasa.gov (Tom Atwater)
Subject: Re: Use of Genetic Algorithms to evolve robot behavior?
Organization: Code 916, NASA Goddard Space Flight Center
Date: Fri, 8 Jan 1993 11:38:40 GMT

In article <C0IK85.C51@world.std.com> btarbox@world.std.com (Brian J Tarbox) writes:
>We trained the simulation in the morning and trained the real dolphinsj
>in the afternoon.  We tried to get the simulation to predict what sort
>of things the real dolphins might do.

So don't leave us hanging -- what were the results?
-- 
Tom Atwater
Newsgroups: comp.ai.genetic
From: bagchi@eecs.umich.edu (Ranjan Drzzzzt!  Bagchi)
Subject: Re: Dr. Dobbs
Organization: Recreational Creationists, Inc.
	<1993Jan10.164614.18016@news.vanderbilt.edu>
Distribution: usa
Date: Sun, 10 Jan 1993 18:28:12 GMT

	Don't suppose anybody's typed in the code yet?  It's not
on the advertized ftp site (ftp.mv.com:/pub/ddj)

	-rj
--
Ranjan Bagchi					       Ranjan.Bagchi@umich.edu
oo   oooo  o oo   ooo oo oo   oo       o o  oooo ooo o       o        oooooooo
Newsgroups: comp.ai.genetic
From: bhonsle@sf49ers.iss.nus.sg (Shailendra K Bhonsle)
Subject: GENESIS 5.0? are there other similar systems?
Keywords: GA, GP, Genetics
Organization: Institute of Systems Science, NUS, Singapore
Date: Wed, 13 Jan 1993 02:17:22 GMT


-- 
Hi,
I am learning about GA through GENESIS 5.0.

Is this the latest version of this system? (It is dated Oct'90)

Are there other similar systems that I can get from ftp sites.



Thanks`


Shailendra K. Bhonsle

(bhonsle@iss.nus.sg)
From: mdlm@great-grain.ai.mit.edu (Michael De-la-Maza)
Newsgroups: comp.ai.genetic
Subject: Sigma truncation fitness function
Date: 9 Jan 1993 21:53:50 GMT
Organization: MIT AI Lab
Distribution: world
NNTP-Posting-Host: great-grain.ai.mit.edu
Keywords: fitness function

On p. 124 of Goldberg (1989), it says that the sigma truncation function
is:

f' = f - (<f> - c*sigma)

      ^^^

On p. 62 of Michalewicz (1992) it says that the sigma truncation
function is:

f' = f + (<f> - c*sigma)

      ^^^

Is it plus or minus?  Goldberg cites Forrest (1985) as the original
source, but I do not have a copy.  Curiously enough, Michalewicz (1992) 
says that he is following Goldberg (1989). 

References

Forrest (1985). Documentation for PRISONERS DILEMMA and NORMS programs
that use the genetic algorithm.  Unpublished manuscript.  University of
Michigan, Ann Arbor.

Goldberg (1989). Genetic algorithms in search, optimization, and machine
learning.  Addison-Wesley.

Michalewicz (1992). Genetic algorithms + data structures = evolution
programs. Springer-Verlag.

Newsgroups: comp.ai.genetic
From: freier@mail.physics.utah.edu (rodney james freier)
Subject: Re: Simple problems to solve genetically
Organization: University of Utah - Physics Department
Date: Mon, 11 Jan 93 16:20:55 GMT

  Hello.  

   As some of you have pointed out, my lengthy analysis of the blackjack
problem overlooked some obvious optimizations.  For example, blackjack does
not care one whit about the suit of the cards, only their value.  So, instead
of needing to keep track of the 52 cards, it only has to keep track of 10
different values.  Then we have:

     Hand's value         9
      dealer's upcard     10
      my first card       10
      my second card      10
      
 for a total of 9000 bits for the strings.  This is actually workable.  For
five cards, the total approaches 10k.  This is pushing it.
    (My insistence on 52 cards is what is technically known as a Brainfart(tm).)

    Some of you have mentioned much simpler counting methods... both simpler
to code and simpler for a human to use in play.   

     I agree that all this work seems to have taken some of the fun out of
making a computer learn.  But I don't believe I have done the significant
learning.   Actually, what I'm doing requires and results in
NO knowledge of when to hit and when to stay.  All I am doing is trying to
make sure that my string pattern can represent ANY conceivable strategy, and
the mechanics of selection then search this space to find effective strategies.

Rod
Newsgroups: comp.ai.genetic
From: steve@monu6.cc.monash.edu.au (Steve Balogh)
Subject: Re: Use of Genetic Algorithms to evolve robot behavior?
Organization: Monash University, Melbourne, AUSTRALIA
Date: Mon, 11 Jan 1993 05:11:38 GMT

In article <C0ICnz.o6@world.std.com> lains@world.std.com (Layne L Ainsworth) writes:
>
>My dream, of course, is a bunch of robots that (who?) could
>continuously clean my house. :-)
>

Of humans?

Steve  :)
Newsgroups: comp.ai.genetic
From: naoursla@eos.ncsu.edu (NORMAN ALAN OURSLAND)
Subject: LISP
Originator: naoursla@c00804-247dan.eos.ncsu.edu
Reply-To: naoursla@eos.ncsu.edu (NORMAN ALAN OURSLAND)
Organization: North Carolina State University, Project Eos
Date: Tue, 12 Jan 1993 15:38:38 GMT


Hi. Does anyone know of a public domain LISP interpreter for UNIX, X-windows,
or MS-DOS to use for playing around with GA? Thank you.

N. Alan Oursland
From: rice@sumex-aim.Stanford.EDU (James Rice)
Newsgroups: comp.ai.genetic
Subject: Re: Use of Genetic Algorithms to evolve robot behavior?
Date: 7 Jan 93 16:43:00
Organization: Knowledge Systems Lab, Stanford University
NNTP-Posting-Host: hpp-ipc-2.stanford.edu
In-reply-to: lains@world.std.com's message of Thu, 7 Jan 1993 23:45:35 GMT

In article <C0ICnz.o6@world.std.com> lains@world.std.com (Layne L Ainsworth) writes:

   Has anyone tried to do this: 

   "Herds" of cheap (really cheap), reprogrammable robots, each loaded
   with one set of the test "chromosome" population of a Genetic
   Algorithm system. They could be evaluated to optimize indivdual
   performance, or "hive" well-being.  Each "generation" would be the
   same robots, with a new generation of "chromosomes" on board.

   Pointers to papers or discussion of the feasibility of such a project
   would both be welcome. I would think this could be a job for the
   much-heralded and -scorned MiniBoard. Wire up all the connections to
   various sensors/actuators and let the herd discover uses for them.

   My dream, of course, is a bunch of robots that (who?) could
   continuously clean my house. :-)

   Thanks.

   -Layne

I don't know of anyone who has done anything like this with real
robots, but I do know of instances of using genetic models to
program robotic behaviour under simulation.

John Koza's "Genetic Programming: On the programming of computers by
means of natural selection" from MIT press (1992) has examples of this
in simulation.

"Genetic Programming - the Movie" Koza & Rice MIT Press 1992 has
visualisations of the learned robotic behaviour.

(Am I beginning to sound like a broken record?)

As well as these I know that Craig Reynolds <cwr@white.sww.symbolics.com>
has been looking at the genetic evolution of flocking/swarm
behaviour.  Koza's book also covers emergent behaviour of ants
(actually it covers 81 different problem domains, so the GP
question is likely to be a reasonable answer to a wide set
of queries similar to your's.  The movie covers >20 diffeent
problem domains).

There's a student at Stanford, whose name escapes me who's
used GP to program Beer's six legged robot.  If you want
I can doubtless dig up a pointer.

Craig Reynolds had a paper at the Simulation of Adaptive Behaviour
conference in Hawaii last month, but I haven't seen it yet.


As of a couple of days ago, there is now a GP mailing list.
Send mail to Genetic-Programming-Request@CS.Stanford.Edu to
subscribe.



Rice.