MiniMax equilibrium of networked differential games

  • Authors:
  • Hui Cao;Emre Ertin;Anish Arora

  • Affiliations:
  • Ohio State University, Columbus, OH;Ohio State University, Columbus, OH;Ohio State University, Columbus, OH

  • Venue:
  • ACM Transactions on Autonomous and Adaptive Systems (TAAS)
  • Year:
  • 2008

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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.