Evolving elementary sight strategies in predators via Genetic

Evolving "elementary sight" strategies in predators via Genetic programming ICBV Project 20. 2. 07 Lior Becker

Goals l l l Witness the evolution of the predator "strategy". Imitate the evolution of the parts in the brain that handle the visual informal interpretation. Try to understand the development stages in the strategy. Try to analyze the usage of the photoreceptors as part of the brain function. Test if the development of sight strategy is a complex process or can be emulated in a computer.

? What is Genetic programming l Bio-Inspired l Inspired by Darwin’s evolutionary principles l J. Koza style

Charles Darwin Principles Competition l Variation l Overproduction l Survival of the fittest l Population adaptation

Genetic programming Main algorithm: 1. Generate the initial population 2. Fitness evaluation 3. Create new generation: – – – 4. Selection Cross Over Mutation Repeat until stop condition

Genetic programming Individual Representation l l Individual is a Scheme-Like Function Represented as a tree (AST)

Genetic programming Recombination - cross over

Predator strategy through GP l World simulator Predator Prey l Process of work l l

Predator l l l GP Brain function Undeveloped eye 15 photoreceptors Moving ability Fitness: catching prey

World simulator & Prey WORLD l l l 2 D world 100*100 Matrix Predator and prey can be at any location PREY l l Static prey Straight Line prey Circle prey Random prey

Process of work 4 Experiments: l l l Evolving 51 generations, different preys Test cases: unlearned preys Plot fitness through time Recording movies Function analysis

Results: straight Line prey

Results: test case l l Test Case Why is it important ?

Results: Fitness vs. generations l l Improvement population adaptation

Results: Function (IFLTE P 6 (PROGN 2(IFLTE P 3 P 11 P 13 )(IFLTE P 2 MAXPP MF P 5 )) (PROGN 2 P 4 P 6 )(IFLTE AP MB P 5 MB )) (PLUS MAXPP P 15 ) (PLUS(IFLTE P 3 P 1 MF P 14 )(IFLTE TR MF P 12 )) (PROGN 2(PLUS P 12 P 10 )(PLUS P 11 TL ))) l Redundancy ? – Dead code. (IFLTE P 6 (IFLTE P 2 MAXPP MF P 5) P 6 (IFLTE AP MB P 5 MB )) (PLUS MAXPP P 15 ) (PLUS(IFLTE P 3 P 1 MF P 14 )(IFLTE TR MF P 12 )) (PLUS P 11 TL )) Pi – photoreceptors; TL – turn left; TR – turn right; MF – move forward.

Results: photo receptors l l l External spreading Why ? Human eye Diff (Rods)

Conclusions & discussion 1. Predator strategy evolvement – – – 2. 3. 4. Random strategy Left/Right circle rotation strategy Combined (Left & Right) strategy External photoreceptors spared out Function redundancy, The key to new life None sophisticated strategies “efficient chase”, why ?

Future work l More realistic 3 D world – – l Obstacles 3 D eye 3 D world Sophisticated preys Co-Evolution, prey and predator

References l l l l Darwin, Charles: On the origin of species by means of natural selection. London, John Murray. (1859) John R. Koza: Genetic Programming: On the programming of computers by natural selection. MIT Press, Cambridge, Mass. (1992) John R. Koza: Genetic Programming II: Automatic Discovery of Reusable Programs. MIT press, Cambridge, Mass. (1994) John R. Koza: Evolution of Subsumption Using Genetic Programming. MIT press, Cambridge, Mass. (1993) Holland, John H. Adaptation in Natural and Artificial Systems. Ann Arbor, MI: University of Michigan Press (1975). Haynes, Sen. : Evolving behavioral strategies in predators and prey, University of Tulsa (1996).

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