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Distributed Artificial Intelligence Meets Machine Learning Learning in Multi-Agent Environments

ECAI'96 Workshop LDAIS, Budapest, Hungary, August 13, 1996, ICMAS'96 Workshop LIOME, Kyoto, Japan, December 10, 1996 Selected Papers

Editors: Weiß, Gerhard (Ed.)

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About this book

The complexity of systems studied in distributed artificial intelligence (DAI), such as multi-agent systems, often makes it extremely difficult or even impossible to correctly and completely specify their behavioral repertoires and dynamics. There is broad agreement that such systems should be equipped with the ability to learn in order to improve their future performance autonomously. The interdisciplinary cooperation of researchers from DAI and machine learning (ML) has established a new and very active area of research and development enjoying steadily increasing attention from both communities. This state-of-the-art report documents current and ongoing developments in the area of learning in DAI systems. It is indispensable reading for anybody active in the area and will serve as a valuable source of information.

Table of contents (18 chapters)

Table of contents (18 chapters)
  • Reader's guide

    Pages 1-10

    Weiß, Gerhard

  • Challenges for machine learning in cooperative information systems

    Pages 11-24

    Singh, Munindar P. (et al.)

  • A modular approach to multi-agent reinforcement learning

    Pages 25-39

    Ono, Norihiko (et al.)

  • Learning real team solutions

    Pages 40-61

    Versino, Cristina (et al.)

  • Learning by linear anticipation in multi-agent systems

    Pages 62-72

    Davidsson, Paul

Buy this book

eBook 58,84 €
price for Spain (gross)
  • The eBook version of this title will be available soon
  • ISBN 978-3-540-69050-4
  • Digitally watermarked, DRM-free
  • Included format:
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Softcover 72,79 €
price for Spain (gross)
  • ISBN 978-3-540-62934-4
  • Free shipping for individuals worldwide
  • Institutional customers should get in touch with their account manager
  • Covid-19 shipping restrictions
  • Usually ready to be dispatched within 3 to 5 business days, if in stock
  • The final prices may differ from the prices shown due to specifics of VAT rules
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Bibliographic Information

Bibliographic Information
Book Title
Distributed Artificial Intelligence Meets Machine Learning Learning in Multi-Agent Environments
Book Subtitle
ECAI'96 Workshop LDAIS, Budapest, Hungary, August 13, 1996, ICMAS'96 Workshop LIOME, Kyoto, Japan, December 10, 1996 Selected Papers
Editors
  • Gerhard Weiß
Series Title
Lecture Notes in Artificial Intelligence
Series Volume
1221
Copyright
1997
Publisher
Springer-Verlag Berlin Heidelberg
Copyright Holder
Springer-Verlag Berlin Heidelberg
eBook ISBN
978-3-540-69050-4
DOI
10.1007/3-540-62934-3
Softcover ISBN
978-3-540-62934-4
Edition Number
1
Number of Pages
XII, 300
Topics