Algorithms and complexity results for graph-based pursuit evasion
Autonomous Robots
Generating strategies for multi-agent pursuit-evasion games in partially observable Euclidean space
Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems - Volume 3
Anytime algorithms for multi-agent visibility-based pursuit-evasion games
Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems - Volume 3
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The pursuit-evasion problem in planar regions is presented, and a strategy based on probability estimation is proposed. The instant evasion routines of the evader are abstracted and described by linear and non-linear probabilistic models. The pursuer computes the capture probabilities of the instant evasion trajectories dynamically to achieve the behaviour process and moving strategy. The proposed strategy takes advantages of evolutionary ideas and estimation of probabilistic distribution approach, and the efficiency and convergence of the strategy in this paper are verified. The simulation experiments show that the proposed approach has better performances on the success rates of capture and the capture time, and the experimental results show that the pursuers can capture the evaders successfully in limited time.