Bubbleworld.evo: Artificial evolution of behavioral decisions in a simulated predator-prey ecosystem.
Thomas Schmickl and Karl Crailsheim
Simulation of Adaptive Behavior 2006 (SAB 2006)
Rome, Italy, 25-29 September 2006
Summary
This article presents a multi-agent simulation of an abstract ecosystem which is inhabited by two species: a predator species and a prey species. Both species show the typical behaviors found in such an ecological relationship that are: hunting behavior and escaping behavior. In the simulation, the actors make behavioral decisions according to “genetically fixed” weighting parameters. These parameters determine which prey item is selected by the predator and which predators are avoided the most by prey. Thus these parameters shape the decisions performed by both species. We incorporated artificial evolution by allowing successful animals to pass their features to their offspring, a process that includes mutation and recombination of these “genes”. The simulation shows that different kinds of optimal behavioral choices emerge out of artificial evolution, when the simulation is run with different physiological and mor-phological parameters of the actors.