群体追逃微分博弈

doi:10.15960/j.cnki.issn.1007-6093.2024.03.003

Abstract

Abstract:

With differential games and classical pursuit-evasion problems as the main focus, this article aims to trace the historical development of group pursuit-evasion differential games. By addressing large-scale group pursuit-evasion issues from the point of mean-field games, the prospects of applying reinforcement learning techniques are elucidated. It proposes exploring solutions to inverse pursuit-evasion differential games, suitable for scenarios such as underwater autonomous vessels, terrestrial robots, and swarms of unmanned aerial vehicles. Diverging from other review papers, it devotes significant attention to the distinctive academic schools of thought in Russia and the former Soviet Union, highlighting their influence in the evolution of this field.

Key words: pursuit-evasion differential games, swarm intelligence games, mean-field games, inverse game theory, reinforcement learning

CLC Number:

O225

Hongwei GAO, Binbin MENG, Jian LIU, Zhaopeng DAI. Group pursuit-evasion differential games[J]. Operations Research Transactions, 2024, 28(3): 46-62.

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