Stochastic multi‐player pursuit–evasion differential games

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AbstractAutonomous aerial vehicles play an important role in military applications such as in search, surveillance and reconnaissance. Multi‐player stochastic pursuit–evasion (PE) differential game is a natural model for such operations involving intelligent moving targets with uncertainties. In this paper, some fundamental issues of stochastic PE games are addressed. We first model a general stochastic multi‐player PE differential game with perfect state information. To avoid the difficulty of multiplicity of the players, we extend the iterative method for deterministic multi‐player PE games to the stochastic case. Starting from certain suboptimal solutions with an improving property, the optimization based on limited look‐ahead can be used for improvement. The process converges when this improvement is applied iteratively. Furthermore, we introduce a hierarchical approach that can determine a valid starting point of the iterative process. As a basis for multi‐player games, stochastic two‐player PE games are also addressed. We also briefly discuss the games with imperfect state information and propose a suboptimal approach from a practical point of view. Finally, we demonstrate the usefulness and the feasibility of the method through simulations. Copyright © 2007 John Wiley & Sons, Ltd.