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An adversarial environment model for bounded rational agents in zero-sum interactions

Authors:

Inon Zuckerman,

Sarit Kraus,

Jeffrey S. Rosenschein,

Gal KaminkaAuthors Info & Claims

AAMAS '07: Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems

Article No.: 83, Pages 1 - 8

https://doi.org/10.1145/1329125.1329226

Published: 14 May 2007 Publication History

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Abstract

Multiagent environments are often not cooperative nor collaborative; in many cases, agents have conflicting interests, leading to adversarial interactions. This paper presents a formal Adversarial Environment model for bounded rational agents operating in a zero-sum environment. In such environments, attempts to use classical utility-based search methods can raise a variety of difficulties (e.g., implicitly modeling the opponent as an omniscient utility maximizer, rather than leveraging a more nuanced, explicit opponent model).

We define an Adversarial Environment by describing the mental states of an agent in such an environment. We then present behavioral axioms that are intended to serve as design principles for building such adversarial agents. We explore the application of our approach by analyzing log files of completed Connect-Four games, and present an empirical analysis of the axioms' appropriateness.

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Cited By

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Liu CCong JYao WZhu E(2024)Playing Extensive Games with Learning of Opponent’s CognitionSensors10.3390/s2404107824:4(1078)Online publication date: 7-Feb-2024
https://doi.org/10.3390/s24041078
Rosenfeld AKraus S(2018)Predicting Human Decision-Making: From Prediction to ActionSynthesis Lectures on Artificial Intelligence and Machine Learning10.2200/S00820ED1V01Y201712AIM03612:1(1-150)Online publication date: 22-Jan-2018
https://doi.org/10.2200/S00820ED1V01Y201712AIM036
Zuckerman IHadad M(2012)The Social LandscapeIEEE Intelligent Systems10.1109/MIS.2012.927:2(36-41)Online publication date: 1-Mar-2012
https://dl.acm.org/doi/10.1109/MIS.2012.9
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Index Terms

An adversarial environment model for bounded rational agents in zero-sum interactions
1. Computing methodologies
  1. Artificial intelligence
    1. Distributed artificial intelligence
2. Theory of computation
  1. Logic
    1. Modal and temporal logics

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Information & Contributors

Information

Published In

AAMAS '07: Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems

May 2007

1585 pages

ISBN:9788190426275

DOI:10.1145/1329125

Conference Chairs:
Edmund Durfee
University of Michigan
,
Makoto Yokoo
Kyushu University
,
Program Chairs:
Michael Huhns
University of South Carolina
,
Onn Shehory
IBM Haifa Research Lab, Israel

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 14 May 2007

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Funding Sources

Israel Science Foundation

Conference

AAMAS07

Sponsor:

AAMAS07: International Conference on Autonomous Agents and Mulitagent Systems

May 14 - 18, 2007

Hawaii, Honolulu

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Overall Acceptance Rate 1,155 of 5,036 submissions, 23%

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Cited By

View all

Liu CCong JYao WZhu E(2024)Playing Extensive Games with Learning of Opponent’s CognitionSensors10.3390/s2404107824:4(1078)Online publication date: 7-Feb-2024
https://doi.org/10.3390/s24041078
Rosenfeld AKraus S(2018)Predicting Human Decision-Making: From Prediction to ActionSynthesis Lectures on Artificial Intelligence and Machine Learning10.2200/S00820ED1V01Y201712AIM03612:1(1-150)Online publication date: 22-Jan-2018
https://doi.org/10.2200/S00820ED1V01Y201712AIM036
Zuckerman IHadad M(2012)The Social LandscapeIEEE Intelligent Systems10.1109/MIS.2012.927:2(36-41)Online publication date: 1-Mar-2012
https://dl.acm.org/doi/10.1109/MIS.2012.9
Zuckerman IKraus SRosenschein J(2012)The adversarial activity model for bounded rational agentsAutonomous Agents and Multi-Agent Systems10.1007/s10458-010-9153-224:3(374-409)Online publication date: 1-May-2012
https://dl.acm.org/doi/10.1007/s10458-010-9153-2
Zuckerman IKraus SRosenschein J(2008)An Empirical Investigation of the Adversarial Activity ModelProceedings of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence10.5555/1567281.1567507(861-862)Online publication date: 27-Jun-2008
https://dl.acm.org/doi/10.5555/1567281.1567507

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