Probabilistic guided exploration for reinforcement learning in self-organizing neural networks

Probabilistic guided exploration for reinforcement learning in self-organizing neural networks

Exploration is essential in reinforcement learning, which expands the search space of potential solutions to a given problem for performance evaluations. Specifically, carefully designed exploration strategy may help the agent learn faster by taking the advantage of what it has learned previously. H...

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書目詳細資料
Main Authors:	Wang, Peng, Zhou, Weigui Jair, Wang, Di, Tan, Ah-Hwee
其他作者:	School of Computer Science and Engineering
格式:	Conference or Workshop Item
語言:	English
出版:	2019
主題:	Reinforcement Learning Self-organizing Neural Networks Engineering::Computer science and engineering
在線閱讀:	https://hdl.handle.net/10356/89871 http://hdl.handle.net/10220/49724
標簽:	添加標簽沒有標簽, 成為第一個標記此記錄!

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