作者: Hironobu Fujiyoshi , Tsubasa Hirakawa , Komei Sugiura , Takayoshi Yamashita , Hidenori Itaya
DOI:
关键词: Action (philosophy) 、 Robot control 、 Artificial intelligence 、 Value (ethics) 、 Reinforcement learning 、 State (computer science) 、 Computer science 、 Feature (machine learning) 、 Focus (computing)
摘要: Deep reinforcement learning (DRL) has great potential for acquiring the optimal action in complex environments such as games and robot control. However, it is difficult to analyze …