Modeling uncertainty in leading ad hoc teams

Noa Agmon, Samuel Barrett, Peter Stone

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

14 Scopus citations

Abstract

Ad hoc teamwork exists when a team of agents needs to cooperate without being able to communicate or use coordination schemes that were designed a-priori. Sometimes ad hoc teamwork amounts to acting so as to bring out the best in your teammates by "leading" them to the optimal joint action. Doing so can be challenging even when their behavior is fully known. In this paper, we take the challenge to the next level by considering the situation in which there is uncertainty about the teammates' behaviors. We discuss the problem of recursive modeling of the teammate's uncertain behavior in two-agent teams and conclude not only that the depth that is useful to model is bounded, but also the number of models useful to consider is linear in the number of actions (and not exponential, as expected). We then show that adopting a naive perspective might lead to negative long-term results in large teams, and thus introduce REACT, an algorithm for determining the action an agent should perform in order to maximize the team's expected utility. Finally, we show empirically that in randomly generated utility matrices, using REACT to select actions outperforms making incorrect assumptions about the identities of teammates.

Original languageEnglish
Title of host publication13th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2014
PublisherInternational Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS)
Pages397-404
Number of pages8
ISBN (Electronic)9781634391313
StatePublished - 2014
Event13th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2014 - Paris, France
Duration: 5 May 20149 May 2014

Publication series

Name13th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2014
Volume1

Conference

Conference13th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2014
Country/TerritoryFrance
CityParis
Period5/05/149/05/14

Bibliographical note

Publisher Copyright:
Copyright © 2014, International Foundation for Autonomous Agents and Multiagent Systems (www.ifaamas.org). All rights reserved.

Funding

FundersFunder number
National Science FoundationCNS-1305287, CNS-1330072
Office of Naval Research21C184-01

    Keywords

    • Agent cooperation
    • Coalition formation
    • Coordination
    • Economic paradigms
    • Game theory (cooperative and non-cooperative)
    • Teamwork

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