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Evolving predator and prey behaviours with co-evolution using genetic programming and decision trees

Developing artificial behaviours to control artificial creatures or vehicles is a task that can be solved by means of Evolutionary Algorithms. The Predator and Prey is a problem where it is possible to evolve behaviours for both predator and prey, using artificial co-evolution: the predator must capture the prey and the prey must evade the predator. Both predator and prey have also different characteristics, the predator is faster and more agile and the prey is slower. This paper presents an alternative, using Genetic Programming with Decision Trees for evolving both Predator and Prey behaviours. The results obtained shows the feasibility of the approach.