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Reinforcement Learning on Monopolistic Intermediary Games: Subject Experiments and Simulation

  • Atsushi Iwasaki
  • Kazuhito Ogawa
  • Makoto Yokoo
  • Sobei H. Oda
Conference paper
Part of the Springer Series on Agent Based Social Systems book series (ABSS, volume 3)

Abstract

Decision making processes of consumers and firms have emerged as a prominent field in multi-agent systems. This approach relaxes the strict assumptions in traditional economic theory. However, little attention has been paid to the validation of the simulation itself, because of the difficulty of acquiring field data which is compared with simulated markets.

Keywords

Reinforcement Learn Demand Function Learn Agent Market Treatment Reinforcement Learn Model 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer 2007

Authors and Affiliations

  • Atsushi Iwasaki
    • 1
  • Kazuhito Ogawa
    • 2
  • Makoto Yokoo
    • 1
  • Sobei H. Oda
    • 3
  1. 1.Kyushu UniversityJapan
  2. 2.Hiroshima City UniversityJapan
  3. 3.Kyoto Sangyo UniversityJapan

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