Agent Strategy Generation by Rule Induction in Predator-Prey Problem

  • Bartłomiej Śnieżyński
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5545)


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.


multi-agent systems rule induction machine learning 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Bartłomiej Śnieżyński
    • 1
  1. 1.Department of Computer ScienceAGH University of Science and TechnologyKrakówPoland

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