Bubbleworld.Evo: Artificial Evolution of Behavioral Decisions in a Simulated Predator-Prey Ecosystem View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2006

AUTHORS

Thomas Schmickl , Karl Crailsheim

ABSTRACT

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 morphological parameters of the actors. More... »

PAGES

594-605

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/11840541_49

DOI

http://dx.doi.org/10.1007/11840541_49

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1033726612


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