Stable and Efficient Policy Evaluation.

Daoming Lyu,Bo Liu,Matthieu Geist,Wen Dong,Saad Biaz,Qi Wang

IEEE Transactions on Neural Networks and Learning Systems（2019）

引用 8|浏览40

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摘要

Policy evaluation algorithms are essential to reinforcement learning due to their ability to predict the performance of a policy. However, there are two long-standing issues lying in this prediction problem that need to be tackled: off-policy stability and on-policy efficiency. The conventional temporal difference (TD) algorithm is known to perform very well in the on-policy setting, yet is not of...

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关键词

Stability criteria,Approximation algorithms,Prediction algorithms,Training,Learning systems

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