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From: sa209@utb.shv.hb.se (Claes Andersson)
Subject: Re: Simulated Environments Parameter Question
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References: <1994Dec5.205450.28653@galileo.cc.rochester.edu> <HIEBELER.94Dec8204448@hershey.harvard.edu> <1994Dec9.170002.11514@galileo.cc.rochester.edu>
Date: Sun, 11 Dec 1994 20:02:51 GMT
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In article <1994Dec9.170002.11514@galileo.cc.rochester.edu> stevens@prodigal.psych.rochester.edu (Greg Stevens) writes:

>In <HIEBELER.94Dec8204448@hershey.harvard.edu> hiebeler@husc.harvard.edu (Dave Hiebeler) writes:
>>In article <1994Dec5.205450.28653@galileo.cc.rochester.edu> stevens@prodigal.psych.rochester.edu (Greg Stevens) writes:

>>>[problems with REGEN_RATE, REPROD_THRESH, WORLD_SIZE, etc.]  
>>> Does anyone know of any hints, other than methodical trial and error,
>>> for discovering good combinations of values for these parameters?

>>  What are the goals of the simulation?  Are you just trying to get
>>stable populations?  Something biologically plausible?

>Well, I wantto get populations stable enough to evolve.  Right now the
>chromosome contains two factors.  First, the food-searching strategy
>of the agents is controlled by a little neural net, which takes as input
>the angle and distance of nearest food (and its own previous output) and
>(through 7 hidden units) outputs a 2-unit, binary coded output for
>movement (00 halt, 01 turn right, 10 turn left, 11 forward).

>This part of the expierment was inspired by on done by Elman and Nolfi where
>they started off with the chromosom controling thr weights, didn't have
>learning of any kind, (therefore in initial generations having random
>search patterns), and saw that through time more and more efficient strategies
>for getting food were evolved (where fitenss was # foods collected).

>I'm doing a spin-odd on that, except I have an additional gene and the 
>following question I want to ask: "Can it be computationally shown that there
>is an evolutionary benefit to there being a weaning period during which the
>child learns from the parent's behaviors?"  The additional gene controls
>the length-in-time-steps of the weaning period, and when a new agent is
>born, the counter moves through that many time steps and for that 
>intercval, the agent copies the parent's movements and uses a supervised
>learning algorithm to hange weights.  After that, no learning takes place.

>I want to see if, when length-of-weaning-period is included in the
>chromosome, there is evolutionary pressure on the length of the weaning
>period.

>But in order to do this, I want the buggers to reproduce for enough generations
>for them to evolve.

>>....  One
>>difference is that in my simulation the "food" (plants) were not
>>deposited randomly down on the grid; new plants appeared when the
>>current ones decided to reproduce (using age-based life-history
>>probability tables -- although after learning something more about
>>plants I realize I should have used size-based tables).  And in fact
>>the new plants were deposited fairly near the parent.  This gave the
>>simulation more spatial structure and heterogeneity.  I got lots of
>>local extinctions in different parts of the lattice, but global
>>extinctions were less common (how much less common depended on the
>>size of the lattice).

>This is interesting and sounds like something I may want to try -- I've
>actually considered it at one point already.

>Greg Stevens

>stevens@prodigal.psych.rochester.edu

 That sounds like a truely interesting project! But I think you should have 
genetic control on how rapid they learn. The weaning period could be a 
period where knowledge is served in a greater tempo. I think you should let 
them learn after that also but slower. Of course, there ought to be a cost 
for having a large brain and a long weaning period, perhaps slower 
reproduction for the mother who has to take care of its offspring. 

Claes Andersson. University of Bors. Sweden
