Open AccessResearch on Inertial Space Intercept Game based on Deep Reinforcement Learning
Author(s) -
Wei Wen-shu,
Bin Wang,
Linjian Hou,
Han Long
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1757/1/012098
Subject(s) - reinforcement learning , inertial frame of reference , space (punctuation) , inertial navigation system , computer science , game theory , artificial intelligence , mathematical optimization , mathematics , mathematical economics , physics , quantum mechanics , operating system
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