Integrated Cooperation and Competition in Multi-Agent Decision-Making

Authors

  • Kyle Wray University of Massachusetts Amherst
  • Akshat Kumar Singapore Management University
  • Shlomo Zilberstein University of Massachusetts Amherst

DOI:

https://doi.org/10.1609/aaai.v32i1.11589

Keywords:

Dec-POMDP, POSG, Multi-Robot Coordination and Competition, Multi-Objective Optimization, Slack

Abstract

Observing that many real-world sequential decision problems are not purely cooperative or purely competitive, we propose a new model—cooperative-competitive process (CCP)—that can simultaneously encapsulate both cooperation and competition. First, we discuss how the CCP model bridges the gap between cooperative and competitive models. Next, we investigate a specific class of group-dominant CCPs, in which agents cooperate to achieve a common goal as their primary objective, while also pursuing individual goals as a secondary objective. We provide an approximate solution for this class of problems that leverages stochastic finite-state controllers. The model is grounded in two multi-robot meeting and box-pushing domains that are implemented in simulation and demonstrated on two real robots.

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Published

2018-04-26

How to Cite

Wray, K., Kumar, A., & Zilberstein, S. (2018). Integrated Cooperation and Competition in Multi-Agent Decision-Making. Proceedings of the AAAI Conference on Artificial Intelligence, 32(1). https://doi.org/10.1609/aaai.v32i1.11589

Issue

Section

AAAI Technical Track: Multiagent Systems