arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2002.11197cs.AIcs.LG

Behavior Cloning in OpenAI using Case Based Reasoning

Carleton University(卡尔顿大学)

Chad Peters, Babak Esfandiari, Mohamad Zalat, Robert West

英文摘要:

Learning from Observation (LfO), also known as Behavioral Cloning, is an approach for building software agents by recording the behavior of an expert (human or artificial) and using the recorded data to generate the required behavior. jLOAF is a platform that uses Case-Based Reasoning to achieve LfO. In this paper we interface jLOAF with the popular OpenAI Gym environment. Our experimental results show how our approach can be used to provide a baseline for comparison in this domain, as well as identify the strengths and weaknesses when dealing with environmental complexity.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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