Can bounded and self-interested agents be teammates? Application to planning in ad hoc teams

Muthukumaran Chandrasekaran, Prashant Doshi, Yifeng Zeng, Yingke Chen

    Research output: Contribution to journalArticlepeer-review

    328 Downloads (Pure)

    Abstract

    Planning for ad hoc teamwork is challenging because it involves agents collaborating without any prior coordination or communication. The focus is on principled methods for a single agent to cooperate with others. This motivates investigating the ad hoc teamwork problem in the context of self-interested decision-making frameworks. Agents engaged in individual decision making in multiagent settings face the task of having to reason about other agents’ actions, which may in turn involve reasoning about others. An established approximation that operationalizes this approach is to bound the infinite nesting from below by introducing level 0 models. For the purposes of this study, individual, self-interested decision making in multiagent settings is modeled using interactive dynamic influence diagrams (I-DID). These are graphical models with the benefit that they naturally offer a factored representation of the problem, allowing agents to ascribe dynamic models to others and reason about them. We demonstrate that an implication of bounded, finitely-nested reasoning by a self-interested agent is that we may not obtain optimal team solutions in cooperative settings, if it is part of a team. We address this limitation by including models at level 0 whose solutions involve reinforcement learning. We show how the learning is integrated into planning in the context of I-DIDs. This facilitates optimal teammate behavior, and we demonstrate its applicability to ad hoc teamwork on several problem domains and configurations
    Original languageEnglish
    Pages (from-to)-
    JournalAutonomous Agents and Multi-Agent Systems
    DOIs
    Publication statusPublished - 23 Nov 2016

    Fingerprint Dive into the research topics of 'Can bounded and self-interested agents be teammates? Application to planning in ad hoc teams'. Together they form a unique fingerprint.

    Cite this