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Evolving "elementary sight" strategies in predators via Genetic programming

Evolving "elementary sight" strategies in predators via Genetic programming. ICBV Project 20.2.07 Lior Becker. Goals. Witness the evolution of the predator "strategy". Imitate the evolution of the parts in the brain that handle the visual informal interpretation .

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Evolving "elementary sight" strategies in predators via Genetic programming

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  1. Evolving "elementary sight" strategies in predatorsviaGenetic programming ICBV Project 20.2.07 Lior Becker

  2. Goals • 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.

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

  4. Charles DarwinPrinciples • Competition • Variation • Overproduction • Survival of the fittest Population adaptation

  5. Genetic programming Main algorithm: • Generate the initial population. • Fitness evaluation. • Create new generation: • Selection. • Cross Over. • Mutation. • Repeat until stop condition.

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

  7. Genetic programmingRecombination - cross over

  8. Predator strategy through GP • World simulator • Predator • Prey • Process of work

  9. Prey • GP. • Brain function. • Undeveloped eye 15 photoreceptors. • Moving ability. • Fitness: catching prey.

  10. Function IFLTE , if less then. PLUS , add 2 num. PROGN2 , run r1 & return r2. TL, turn right, 5 Deg. TR, turn left , 5 Deg. MF, move forward. MB, move backward. Terminals RP, resting potential. AP, action potential. P1 .. P15, photoreceptors , 2 Deg. MAXPP, max value of the photoreceptors. Tree components

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

  12. Process of work • Evolving 51 generations, different preys. • Test cases: unlearned preys. • Plot fitness through time. • Recording movies. • Function analysis.

  13. Results: straight Line prey

  14. Results: test case • Test Case • Why is it important ?

  15. Results: Fitness vs. generations • Improvement. • population adaptation.

  16. Results: Function (IFLTE (IFLTE P6 (PROGN2(IFLTE P3 P11 P13 P13 )(IFLTE P2 MAXPP MF P5 )) (PROGN2 P4 P6 )(IFLTE AP MB P5 MB )) (PLUS MAXPP P15 ) (PLUS(IFLTE P3 P1 MF P14 )(IFLTE TR MF P1 P12 )) (PROGN2(PLUS P12 P10 )(PLUS P11 TL ))) • Redundancy ? – Dead code. (IFLTE (IFLTE P6 (IFLTE P2 MAXPP MFP5) P6 (IFLTE AP MB P5 MB )) (PLUS MAXPP P15 ) (PLUS(IFLTE P3P1MFP14 )(IFLTE TR MFP1P12 )) (PLUS P11TL )) Pi – photoreceptors; TL – turn left; TR – turn right; MF – move forward.

  17. Results: photo receptors • External spreading. • Why ?? • Human eye Diff.

  18. Conclusions & discussion • Predator strategy evolvement. • 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 ?

  19. Future work • More realistic 3D world. • Obstacles. • 3D eye • 3D world • Sophisticated preys. • Co-Evolution, prey and predator.

  20. References • 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).

  21. Movie Data Base

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