title: Kernel Recursive Least-Squares Temporal Difference Algorithms with Sparsification and Regularization.
abstract: By combining with sparse kernel methods, least-squares temporal difference (LSTD) algorithms can construct the feature dictionary automatically and obtain a better generalization ability. However, the previous kernel-based LSTD algorithms do not consider regularization and their sparsification processes are batch or offline, which hinder their widespread applications in online learning problems. In this paper, we combine the following five techniques and propose two novel kernel recursive LSTD algorithms: (i) online sparsification, which can cope with unknown state regions and be used for online learning, (ii) L 2 and L 1 regularization, which can avoid overfitting and eliminate the influence of noise, (iii) recursive least squares, which can eliminate matrix-inversion operations and reduce computational complexity, (iv) a sliding-window approach, which can avoid caching all history samples and reduce the computational cost, and (v) the fixed-point subiteration and online pruning, which can make L 1 regularization easy to implement. Finally, simulation results on two 50-state chain problems demonstrate the effectiveness of our algorithms.
authors.affiliation: School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China; College of Information Science and Technology, Hainan University, Haikou 570228, China.
authors.forename: Chunyuan
authors.identifier: 0000-0001-8297-9803
authors.initials: C
authors.lastname: Zhang
authors.affiliation: School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China.
authors.forename: Qingxin
authors.initials: Q
authors.lastname: Zhu
authors.affiliation: School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China.
authors.forename: Xinzheng
authors.initials: X
authors.lastname: Niu
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D003198:Computer Simulation; D006801:Humans; D007858:Learning / Q000502:physiology*; D009862:Online Systems