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Description
  • We present a description of our multi-agent system where computational intelligence methods are embodied as software agents. This system is designed in order to allow easy experiments with learning, meta learning, gathering experience based on previous computations, and recommending suitable methods for particular data. The architecture of the system is presented and its meta learning abilities are demonstrated on a set of experiments with neural network models and both evolutionary and local search heuristics.
  • We present a description of our multi-agent system where computational intelligence methods are embodied as software agents. This system is designed in order to allow easy experiments with learning, meta learning, gathering experience based on previous computations, and recommending suitable methods for particular data. The architecture of the system is presented and its meta learning abilities are demonstrated on a set of experiments with neural network models and both evolutionary and local search heuristics. (en)
Title
  • A Novel Meta Learning System and Its Application to Optimization of Computing Agents' Results
  • A Novel Meta Learning System and Its Application to Optimization of Computing Agents' Results (en)
skos:prefLabel
  • A Novel Meta Learning System and Its Application to Optimization of Computing Agents' Results
  • A Novel Meta Learning System and Its Application to Optimization of Computing Agents' Results (en)
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  • RIV/00216208:11320/13:10194236!RIV14-MSM-11320___
http://linked.open...avai/predkladatel
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  • S
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  • 58908
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  • RIV/00216208:11320/13:10194236
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  • roles; ontology; multi-agent system; meta-learning; data-mining (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [5BA65C81D2F1]
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  • Macau
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  • Los Alamitos, USA
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  • Proceedings of the 2012 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology Workshops, vol. 2
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  • Neruda, Roman
  • Kazík, Ondřej
  • Pešková, Klára
  • Pilát, Martin
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http://linked.open.../riv/zahajeniAkce
number of pages
http://bibframe.org/vocab/doi
  • 10.1109/WI-IAT.2012.250
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  • IEEE Computer Society
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  • 978-1-4673-6057-9
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  • 11320
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