Evolving "elementary sight" strategies in predators via Genetic programming ICBV Project 20.2.07...
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Transcript of Evolving "elementary sight" strategies in predators via Genetic programming ICBV Project 20.2.07...
Evolving "elementary sight" strategies in predators
viaGenetic 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. 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?
Bio-InspiredBio-Inspired
Inspired by Darwin’s evolutionary
principles
J.Koza style.
Charles DarwinPrinciples
CompetitionVariationOverproductionSurvival of the fittest
Population adaptation
Genetic programming
Main algorithm:1. Generate the initial population.2. Fitness evaluation.3. Create new generation:
– Selection.– Cross Over.– Mutation.
4. Repeat until stop condition.
Genetic programming Individual Representation
Individual is a Scheme-Like Function Represented as a tree (AST).
Tree components
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.
World simulator & Prey
WORLD
2D world. 100*100 Matrix. Predator and prey can
be at any location.
PREY
Static prey. Straight Line prey Circle prey Random prey.
Process of work
Evolving 51 generations, different preys. Test cases: unlearned preys. Plot fitness through time. Recording movies. Function analysis.
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 MF P5) P6 (IFLTE AP MB P5 MB )) (PLUS MAXPP P15 ) (PLUS(IFLTE P3 P1 MF P14 )(IFLTE TR MF P1 P12 )) (PLUS P11 TL ))Pi – photoreceptors; TL – turn left; TR – turn right; MF – move forward.
Conclusions & discussion
1. Predator strategy evolvement.– Random strategy– Left/Right circle rotation strategy.– Combined (Left & Right) strategy.
2. External photoreceptors spared out.3. Function redundancy, The key to new life.4. None sophisticated strategies
“efficient chase”, why ?
Future work
More realistic 3D world.– Obstacles.– 3D eye– 3D world– Sophisticated preys.
Co-Evolution, prey and predator.
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).