Social learning and Bayesian games in multiagent signal processing: How do local and global decision makers interact?

Vikram Krishnamurthy, H. Vincent Poor

Research output: Contribution to journalArticle

41 Scopus citations

Abstract

How do local agents and global decision makers interact in statistical signal processing problems where autonomous decisions need to be made? When individual agents possess limited sensing, computation, and communication capabilities, can a network of agents achieve sophisticated global behavior? Social learning and Bayesian games are natural settings for addressing these questions. This article presents an overview, novel insights, and a discussion of social learning and Bayesian games in adaptive sensing problems when agents communicate over a network. Two highly stylized examples that demonstrate to the reader the ubiquitous nature of the models, algorithms, and analysis in statistical signal processing are discussed in tutorial fashion.

Original languageEnglish (US)
Article number6494678
Pages (from-to)43-57
Number of pages15
JournalIEEE Signal Processing Magazine
Volume30
Issue number3
DOIs
StatePublished - 2013

All Science Journal Classification (ASJC) codes

  • Signal Processing
  • Electrical and Electronic Engineering
  • Applied Mathematics

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