Efficient Communication for Pursuit-Evasion Games with Asymmetric Information
Dipankar Maity

TL;DR
This paper analyzes pursuit-evasion differential games with asymmetric information, focusing on optimal control and communication strategies when a static sensor intermittently transmits location data, revealing strategic trade-offs and implicit communication effects.
Contribution
It derives Nash equilibrium strategies for control and communication in pursuit-evasion games with limited sensor transmissions and explores implicit communication phenomena.
Findings
Optimal control strategies for pursuer and evader derived.
Optimal intermittent communication strategy identified.
Implicit communication effects analyzed.
Abstract
We consider a class of pursuit-evasion differential games in which the evader has continuous access to the pursuer's location, but not vice-versa. There is an immobile sensor (e.g., a ground radar station) that can sense the evader's location and communicate that information intermittently to the pursuer. Transmitting the information from the sensor to the pursuer is costly and only a finite number of transmissions can happen throughout the entire game. The outcome of the game is determined by the control strategies of the players and the communication strategy between the sensor and the pursuer. We obtain the (Nash) equilibrium control strategies for both the players as well as the optimal communication strategy between the static sensor and the pursuer. We discuss a dilemma for the evader that emerges in this game. We also discuss the emergence of implicit communication where the…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsGuidance and Control Systems · Quantum chaos and dynamical systems · Stability and Controllability of Differential Equations
