适应性查询用于从人类反中学习奖励

Yashwanthi Anand1, Nnamdi Nwagwu1, Kevin Sabbe1

  • 1Oregon State University, Corvallis, OR, United States.

PubMed
概括

本研究介绍了自适应反选择,以训练使用多种人类反格式的机器人. 这种方法优化了查询状态和反类型,以实现更高效和与用户一致的机器人学习,提高安全性和适应性.

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Reinforcement01:23

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