Abstract
Aiming at the problem of the intercept game in the inertial space, this paper builds a model of basic actions of the two sides of the intercept game in the inertial space, explored the applicability of Deep Reinforcement Learning in inertial space game problem-solving. Based on Proximal Policy Optimization (PPO), this inertial space game problem is solved and the optimal solution is obtained by the reward designing with cumulative miss distance and minimum distance respectively, and finally, the effectiveness of the algorithm based on PPO is verified through the game simulation and results from comparison
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