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A Systematic Approach for Including Machine Learning in Multi-agent Systems

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Agent-Oriented Information Systems II (AOIS 2004)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3508))

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Abstract

Large scale multi-agent systems (MASs) in unpredictable environments must use machine learning techniques to perform their goals and improve the performance of the system. This paper presents a systematic approach to introduce machine learning in the design and implementation phases of a software agent. We also present an incremental implementation process for building asynchronous and distributed agents, which suppors the combination of machine learning strategies. This process supports the stepwise building of adaptable MASs for unknown situations, improving their capacity to scale up. We use the Trading Agent Competition (TAC) environment as a case study to illustrate the suitability of our approach.

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Authors and Affiliations

  1. TecComm Group (LES),Computer Science Department, PUC-Rio, Rua Marques de São Vicente 225, Gávea, Rio de Janeiro, Brazil

    José A. R. P. Sardinha, Alessandro Garcia, Carlos J. P. Lucena & Ruy L. Milidiú

Authors
  1. José A. R. P. Sardinha
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  2. Alessandro Garcia
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  3. Carlos J. P. Lucena
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  4. Ruy L. Milidiú
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Editor information

Editors and Affiliations

  1. DG Information Society and Media, Unit D3: Software Technologies, European Commission, Avenue de Beaulieu 29, level 4, office 49, 1049, Brussels, Belgium

    Paolo Bresciani

  2. DISI, University of Trento, 38100, Povo, Trento, Italy

    Paolo Giorgini

  3. Faculty of Information Technology, University of Technology, Sydney, 2000, Broadway, NSW, Australia

    Brian Henderson-Sellers

  4. School of Information Management and Technology Management, University of New South Wales, Australia

    Graham Low

  5. Higher Education Development Centre, University of Otago, P.O. Box 56, Dunedin, New Zealand

    Michael Winikoff

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© 2005 Springer-Verlag Berlin Heidelberg

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Sardinha, J.A.R.P., Garcia, A., Lucena, C.J.P., Milidiú, R.L. (2005). A Systematic Approach for Including Machine Learning in Multi-agent Systems. In: Bresciani, P., Giorgini, P., Henderson-Sellers, B., Low, G., Winikoff, M. (eds) Agent-Oriented Information Systems II. AOIS 2004. Lecture Notes in Computer Science(), vol 3508. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11426714_14

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  • DOI: https://doi.org/10.1007/11426714_14

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-25911-4

  • Online ISBN: 978-3-540-31946-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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