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This paper proposed a pursuit-evasion algorithm based on the Option method from hierarchical reinforcement learning and applied it into multi-robot pursuit-evasion game in 2D-Dynamic environment. The algorithm efficiency is studied by comparing it with Q-learning. We decompose the complex task with option method, and divide the learning process into two parts: High-level learning and Low-level learning,...
Algorithms based on game theory regard the equilibriums as the optimal solution for the cooperation in multi-agent system (MAS), especially the evolutionary stable equilibriums (ESE) had been studied because they can give a consistent optimal solution for the MAS and partly solve the equilibrium selection problem of game theory. However ESE is dynamic stable, so the strategy of every agent keeps on...
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