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MiniMax equilibrium of networked differential games

Published:12 December 2008Publication History
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Abstract

Surveillance systems based on wireless sensor network technology have been shown to successfully detect, classify and track evaders over a large area. State information collected via the sensor network also enables these systems to actuate mobile agents so as to achieve surveillance goals, such as target capture and asset protection. But satisfying these goals is complicated by the fact that the track information in a sensor network is routed to mobile agents through multihop wireless communication links and is thus subject to message delays and losses. Stabilization must also be considered in designing pursuer strategies so as to deal with state corruption as well as suboptimal evader strategies.

In this article, we formulate optimal pursuit control strategies in the presence of network effects, assuming that target track information has been established locally in the sensor network. We adapt ideas from the theory of differential games to networked games—including ones involving nonperiodic track updates, message losses and message delays—to derive optimal strategies, bounds on the information requirements, and scaling properties of these bounds. We show the inherent stabilization features of our pursuit strategies, both in terms of implementation as well as the strategies themselves.

References

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  1. MiniMax equilibrium of networked differential games

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      • Published in

        cover image ACM Transactions on Autonomous and Adaptive Systems
        ACM Transactions on Autonomous and Adaptive Systems  Volume 3, Issue 4
        November 2008
        171 pages
        ISSN:1556-4665
        EISSN:1556-4703
        DOI:10.1145/1452001
        Issue’s Table of Contents

        Copyright © 2008 ACM

        Publisher

        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 12 December 2008
        • Accepted: 1 September 2008
        • Revised: 1 July 2008
        • Received: 1 March 2007
        Published in taas Volume 3, Issue 4

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