Evolving decision strategies for computational intelligence agents

Authors:
Roman Neruda;Martin Šlapák
Affiliations:
Institute of Computer Science, Academy of Sciences of the Czech Republic, Prague 8, Czech Republic;Department of Theoretical Computer Science, Faculty of Information Technology CTU in Prague, Czech Republic, Prague 6, Czech Republic
Venue:
ICIC'12 Proceedings of the 8th international conference on Intelligent Computing Theories and Applications
Year:
2012

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Abstract

An adaptive control system for computational intelligence agent within a data mining multi-agent system is presented. As opposed to other approaches concerning a fixed control mechanism, the presented approach is based on evolutionary trained decission trees. This leads to control approach created adaptively based on data tasks the agent encounters during its adaptive phase. A pilot implementation within a JADE-based data mining system illustrates the suitability of such approach.