An Introduction to Pursuit-evasion Differential Games
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Abstract (arXiv)
Pursuit and evasion conflicts represent challenging problems with important applications in aerospace and robotics. In pursuit-evasion problems, synthesis of intelligent actions must consider the adversary's potential strategies. Differential game theory provides an adequate framework to analyze possible outcomes of the conflict without assuming particular behaviors by the opponent. This article presents an organized introduction of pursuit-evasion differential games with an overview of recent advances in the area. First, a summary of the seminal work is outlined, highlighting important contributions. Next, more recent results are described by employing a classification based on the number of players: one-pursuer-one-evader, N-pursuers-one-evader, one-pursuer-M-evaders, and N-pursuer-M-evader games. In each scenario, a brief summary of the literature is presented. Finally, two representative pursuit-evasion differential games are studied in detail: the two-cutters and fugitive ship differential game and the active target defense differential game. These problems provide two important applications and, more importantly, they give great insight into the realization of cooperation between friendly agents in order to form a team and defeat the adversary.
Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). First posted on arXiv 10 Mar 2020.
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Citing papers per year: 2022: 2; 2023: 0; 2024: 0; 2025: 3; 2026: 1.
6 papers.
- 2022A Survey of Decision Making in Adversarial Gamescited by 3
- 2022Toward multi-target self-organizing pursuit in a partially observable Markov gamecited by 2
- 2025TERL: Large-Scale Multi-Target Encirclement Using Transformer-Enhanced Reinforcement Learningcited by 1
- 2025Strategic Communication under Threat: Learning Information Trade-offs in Pursuit-Evasion Gamescited by 0
- 2025Fast and the Furious: Hot Starts in Pursuit-Evasion Gamescited by 0
- 2026Game-Theory-Assisted Reinforcement Learning for Border Defense: Early Termination based on Analytical Solutionscited by 0
- 2026Game-Theory-Assisted Reinforcement Learning for Border Defense: Early Termination based on Analytical Solutions16 Mar 2026
- 2025Fast and the Furious: Hot Starts in Pursuit-Evasion Games12 Oct 2025
- 2025Strategic Communication under Threat: Learning Information Trade-offs in Pursuit-Evasion Games9 Oct 2025
- 2025TERL: Large-Scale Multi-Target Encirclement Using Transformer-Enhanced Reinforcement Learning16 Mar 2025
- 2022A Survey of Decision Making in Adversarial Games16 Jul 2022
- 2022Toward multi-target self-organizing pursuit in a partially observable Markov game24 Jun 2022