Opposition-based Q(ℷ) algorithm

被引：0

作者：

Shokri, Maryam ^{[1
]}

Tizhooshl, Hamid R. ^{[1
]}

Kamel, Mohamed ^{[2
]}

机构：

[1] Univ Waterloo, Dept Syst Design Engn, Pattern Anal & Machine Intelligence Lab, 200 Univ Ave W, Waterloo, ON N2L 3G1, Canada

[2] Univ Waterloo, Dept Elect & Comp Engn, Waterloo, ON N2L 3G1, Canada

来源：

2006 IEEE INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORK PROCEEDINGS, VOLS 1-10 | 2006年

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The problem of delayed reward in reinforcement learning is usually tackled by implementing the mechanism of eligibility traces. In this paper we introduce an extension of eligibility traces to solve one of the challenging problems in reinforcement learning. The concept of opposition traces is proposed in this work to deal with large state space problems in reinforcement learning applications. We combine the idea of opposition and eligibility traces to construct the opposition-based Q(lambda). The results are compared with the conventional Watkins' Q(lambda) and reflect a remarkable performance increase.

引用

页码：254 / +

页数：2

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