Multi-agent learning for engineers

Shie Mannor, Jeff S. Shamma*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

37 Scopus citations

Abstract

As suggested by the title of Shoham, Powers, and Grenager's position paper [Y. Shoham, R. Powers, T. Grenager, If multi-agent learning is the answer, what is the question? Artificial Intelligence 171 (7) (2007) 365-377, this issue], the ultimate lens through which the multi-agent learning framework should be assessed is "what is the question?". In this paper, we address this question by presenting challenges motivated by engineering applications and discussing the potential appeal of multi-agent learning to meet these challenges. Moreover, we highlight various differences in the underlying assumptions and issues of concern that generally distinguish engineering applications from models that are typically considered in the economic game theory literature.

Original languageEnglish (US)
Pages (from-to)417-422
Number of pages6
JournalArtificial Intelligence
Volume171
Issue number7
DOIs
StatePublished - May 1 2007

Keywords

  • Cooperative control
  • Distributed control
  • Learning in games
  • Multi-agent systems
  • Nash equilibrium

ASJC Scopus subject areas

  • Language and Linguistics
  • Linguistics and Language
  • Artificial Intelligence

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