Residual Sarsa algorithm with function approximation

In this work, we proposed an efficient algorithm named the residual Sarsa algorithm with function approximation (FARS) to improve the performance of the traditional Sarsa algorithm, and we use the gradient-descent method to update the function parameter vector. In the learning process, the Bellman r...

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Vydané v:	Cluster computing Ročník 22; číslo Suppl 1; s. 795 - 807
Hlavní autori:	Qiming, Fu, Wen, Hu, Quan, Liu, Heng, Luo, Lingyao, Hu, Jianping, Chen
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York Springer US 01.01.2019 Springer Nature B.V
Predmet:	Algorithms Approximation Computer Communication Networks Computer Science Convergence Distance learning Fuzzy logic Machine learning Mathematical analysis Operating Systems Performance enhancement Processor Architectures Sarsa algorithm Gradient descent Function approximation Bellman residual Reinforcement learning
ISSN:	1386-7857, 1573-7543
On-line prístup:	Získať plný text
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