An adaptive-learning framework for semi-cooperative multi-agent coordination

Abdeslem Boukhtouta, Jean Berger, Warren Buckler Powell, Abraham George

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

Complex problems involving multiple agents exhibit varying degrees of cooperation. The levels of cooperation might reflect both differences in information as well as differences in goals. In this research, we develop a general mathematical model for distributed, semi-cooperative planning and suggest a solution strategy which involves decomposing the system into subproblems, each of which is specified at a certain period in time and controlled by an agent. The agents communicate marginal values of resources to each other, possibly with distortion. We design experiments to demonstrate the benefits of communication between the agents and show that, with communication, the solution quality approaches that of the ideal situation where the entire problem is controlled by a single agent.

Original languageEnglish (US)
Title of host publicationIEEE SSCI 2011
Subtitle of host publicationSymposium Series on Computational Intelligence - ADPRL 2011: 2011 IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning
Pages324-331
Number of pages8
DOIs
StatePublished - Sep 5 2011
EventSymposium Series on Computational Intelligence, IEEE SSCI2011 - 2011 IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning, ADPRL 2011 - Paris, France
Duration: Apr 11 2011Apr 15 2011

Publication series

NameIEEE SSCI 2011: Symposium Series on Computational Intelligence - ADPRL 2011: 2011 IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning

Other

OtherSymposium Series on Computational Intelligence, IEEE SSCI2011 - 2011 IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning, ADPRL 2011
CountryFrance
CityParis
Period4/11/114/15/11

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Software

Keywords

  • Multi-agent
  • approximate dynamic programming
  • cooperative
  • learning

Fingerprint Dive into the research topics of 'An adaptive-learning framework for semi-cooperative multi-agent coordination'. Together they form a unique fingerprint.

  • Cite this

    Boukhtouta, A., Berger, J., Powell, W. B., & George, A. (2011). An adaptive-learning framework for semi-cooperative multi-agent coordination. In IEEE SSCI 2011: Symposium Series on Computational Intelligence - ADPRL 2011: 2011 IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning (pp. 324-331). [5967386] (IEEE SSCI 2011: Symposium Series on Computational Intelligence - ADPRL 2011: 2011 IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning). https://doi.org/10.1109/ADPRL.2011.5967386