[net.cog-eng] animal rule-systems simulations

g451252772ea@deneb.UUCP (10/14/86)

*** REPLACE THIS LINE WITH YOUR MESSAGE ***
By way of introduction to the following Mail message, 'bc' posted last
spring a query for anyone with references on 'simulation animal behavior using
rule-driven systems'.  I discovered his message in an old listing, and find
the topic of interest also.  In case 'bc' (William Coderre) is no longer
at mit-amt.MIT.EDU, I'm posting to the net also.  Thanks for your tolerance...


     Hi, bc (?bc?):

     I'm curious about any replies you got to your query last April for
rule-driven simulations of animal behaviors.  I have somewhat
similar interests, reflecting my grad work in ethology here at Davis, and my
undergrad work at U.C. Santa Cruz in Information- Computer science.  We have
here a person doing stuff you'd enjoy: Marc Mangel, with his 'dynamic
stochastic optimization' analysis of everything from insect oviposition
choices to foraging theory to fisheries harvesting.  His insight seems to be
the addition of a 'state variable' - usually characterized as energy
reserves, gut contents or similar - to revamp the static optimization models
of Houston, McNamara, Krebs, et al. (the 'Oxford' crowd).  Mangel is chair
of the math dept. here, and co-authors with Colin Clark of the U. British
Columbia.  Clark is visiting here this quarter and giving an applied math
seminar, with lots of application studies.  Both guys emphasize computer
programs, and the programs have a game-like air to them. If you'd like more
info, I can send some typed notes by Mangel describing the analysis, and one
of his most counter-intuitive applications.

     Mostly I'm working with evolutionary studies: the predator/prey
interactions of snakes and ground squirrels (my thesis is on stupidity: the
dumbness of Arctic ground squirrels, which don't even appear to <recognize>
snakes of any kind, much less handle them correctly).  I do have to give a 
week's worth of lectures to my animal-behavior group next month, explaining 
'artificial intelligence' ab initio to them.  Despite Mangel and Clark, the 
prejudice against math/systems here is substantial.  Any ideas you have for 
good material/examples, in the vein of Winograd's new book or Rosen's 
discussion of ANTICIPATORY SYSTEMS (much watered down!) or ANYTHING else,
would be most welcome!

     Thanks --Ron.