Agent Strategy Generation by Rule Induction in Predator-Prey Problem

Authors:
Bartłomiej Śnieżyński
Affiliations:
Department of Computer Science, AGH University of Science and Technology, Kraków, Poland
Venue:
ICCS 2009 Proceedings of the 9th International Conference on Computational Science
Year:
2009

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Abstract

This paper contains a proposal of application of rule induction for generating agent strategy. This method of learning is tested on a predator-prey domain, in which predator agents learn how to capture preys. We assume that proposed learning mechanism will be beneficial in all domains, in which agents can determine direct results of their actions. Experimental results show that the learning process is fast. Multi-agent communication aspect is also taken into account. We can show that in specific conditions transferring learned rules gives profits to the learning agents.