Value approximation with least squares support vector machine in reinforcement learning system

Journal of Computational and Theoretical Nanoscience

Volumn 4, Issue 7-8, 2007, Pages 1290-1294

  Wang, Xuesong ^a   Tian, Xilan ^a   Cheng, Yuhu ^a  

^a CHINA UNIVERSITY OF MINING AND TECHNOLOGY   (China)

Author keywords

Boltzmann Gibbs distribution; Least squares support vector machine; Reinforcement learning; Value approximation

Indexed keywords

DEEP NEURAL NETWORKS; LEARNING SYSTEMS; LEAST SQUARES APPROXIMATIONS; SIMULATED ANNEALING; STOCHASTIC SYSTEMS; SUPPORT VECTOR MACHINES; VECTOR SPACES; VECTORS;

BOLTZMANN-GIBBS DISTRIBUTION; CONTINUOUS STATE SPACE; LEARNING EFFICIENCY; LEAST SQUARES SUPPORT VECTOR MACHINES; SIMULATED ANNEALING METHOD; SLIDING TIME WINDOWS; TEMPERATURE VALUES; VALUE APPROXIMATION;

REINFORCEMENT LEARNING;

EID: 47149095559     PISSN: 15461955     EISSN: None     Source Type: Journal    
DOI: 10.1166/jctn.2007.2413     Document Type: Article

References (11)

1. C. J. C. H. Watkins and P. Dayan, Machine Learning 8, 279 (1992).
2. K. Samejima and T. Omori, Neural Networks 12, 1143 (1999).
3. S. F. Su and S. H. Hsieh, IEEE Transactions on Systems, Man and Cybernetics 32, 645 (2002).
4. I. S. K. Lee and H. Y. K. Lau, Engineering Applications of Artificial Intelligence 17, 577 (2004).
5. M. J. Er and C. Deng, IEEE Transactions on Industrial Electronics 52, 898 (2005).
6. X. S. Wang, Y. H. Cheng, and W. Sun, Q Learning Based on Self-Organizing Fuzzy Radial Basis Function Network, Lecture Notes in Computer Science, Springer-Verlag, Berlin, Heidelberg, New York (2066), Vol. 3971, pp. 607-615.
7. V. Vapnik, The Nature of Statistical Learning Theory, Springer Verlag, Berlin (1995).
8. D. Schneegab, S. Udluft, and T. Martinetz, Proceedings of the 24th IASTED International Multi-Conference on Artificial Intelligence and Applications (2006), pp. 428-433.
9. J. A. K. Suykens and J. Vandewalle, Neural Processing Letters 9, 293 (1999).
10. L. P. Kaelbling, M. L. Littman, and A. W. Moore, Journal of Artificial Intelligence Research 4, 237 (1996).
11. W. W. Yan, J. L. Chang, and H. H. Shao, Journal of Shanghai Jiaotong University (In Chinese) 38, 524 (2004).