0384818 - ÚI 2013 RIV DE eng C - Conference Paper (international conference)
Neruda, Roman - Šlapák, M.
Evolving Decision Strategies for Computational Intelligence Agents.
Intelligent Computing Theories and Applications. Berlin: Springer, 2012 - (Huang, D.; Ma, J.; Jo, K.; Gromiha, M.), s. 213-220. Lecture Notes in Artificial Intelligence, 7390. ISBN 978-3-642-31575-6. ISSN 0302-9743.
[ICIC 2012. Intelligent Computing Theories and Applications. International Conference /8./. Huangshan (CN), 25.07.2012-29.07.2012]
R&D Projects: GA ČR GAP202/11/1368
Institutional support: RVO:67985807
Keywords : computational intelligence * genetic programming * intelligent agents
Subject RIV: IN - Informatics, Computer Science
DOI: https://doi.org/10.1007/978-3-642-31576-3_28

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.
Permanent Link: http://hdl.handle.net/11104/0007336