Adaptive dynamic programming with balanced weights seeking strategy

IEEE SSCI 2011: Symposium Series on Computational Intelligence - ADPRL 2011: 2011 IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning

Volumn , Issue , 2011, Pages 210-217

  Fu, Jian ^a   He, Haibo ^b   Ni, Zhen ^b  

^a WUHAN UNIVERSITY OF TECHNOLOGY   (China)

^b The University of Rhode Island   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ACTION NETWORK; ADAPTIVE CONTROL; ADAPTIVE DYNAMIC PROGRAMMING; COMPARATIVE STUDIES; CONTROL STRATEGIES; CRITIC NETWORK; INVERTED PENDULUM; LEVENBERG-MARQUARDT; LEVENBERG-MARQUARDT METHOD; NOISE CONDITIONS; ONLINE LEARNING; UPDATING STRATEGY;

ARTIFICIAL INTELLIGENCE; E-LEARNING; LEARNING ALGORITHMS; REINFORCEMENT LEARNING;

DYNAMIC PROGRAMMING;

EID: 80052225230     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ADPRL.2011.5967373     Document Type: Conference Paper

References (15)

1. P. J. Werbos, "Adp: The key direction for future research in intelligent control and understanding brain intelligence," IEEE Transactions on Systems Man and Cybernetics Part B-Cybernetics, vol. 38, no. 4, pp. 898-900, 2008.
2. P. J. Werbos, "Intelligence in the brain: A theory of how it works and how to build it," Neural Networks, vol. 22, no. 3, pp. 200-212, 2009.
3. D. Bertsekas and J. Tsitsiklis, "Neuro-dynamic programming: an overview," in Proceedings of the 34th IEEE Conference on Decision and Control, vol. 1, 1995, pp. 560-564.
4. D. Prokhorov and D. Wunsch, "Adaptive critic designs," IEEE Transactions on Neural Networks, vol. 8, no. 5, pp. 997-1007, 1997. (Pubitemid 127763331)
5. F.-Y. Wang, H. Zhang, and D. Liu, "Adaptive dynamic programming: An introduction," Computational Intelligence Magazine, IEEE, vol. 4, no. 2, pp. 39-47, 2009.
6. J. Si and W. Yu-Tsung, "Online learning control by association and reinforcement," Neural Networks, IEEE Transactions on, vol. 12, no. 2, pp. 264-276, 2001. (Pubitemid 32371483)
7. J. J. Murray, C. J. Cox, G. G. Lendaris, and R. Saeks, "Adaptive dynamic programming," IEEE Transactions on Systems Man and Cybernetics Part C-Applications and Reviews, vol. 32, no. 2, pp. 140-153, 2002. (Pubitemid 35289398)
8. H. He and B. Liu, "A hierarchical learning architecture with multiplegoal representations based on adaptive dynamic programming," Proc. IEEE International Conference on Networking, Sensing, and Control (ICNSC'10), pp. 286-291, 2010.
9. R. Bellman, Dynaimic programming. Princeton University Press, 1957.
10. W. Powell, Approximate Dynamic Programming: Solving the curses of dimensionality. Wiley-Blackwell, 2007.
11. P. J. Werbos, "Backpropagation through time: What it does and how to do it," Proceedings of the IEEE, vol. 78, no. 10, pp. 1550-1560, 2002.
12. J. Y. Fan and Y. X. Yuan, "On the quadratic convergence of the levenberg-marquardt method without nonsingularity assumption," Computing, vol. 74, no. 1, pp. 23-39, 2005.
13. H. Nielsen. (1999) Damping parameter in marquardt's method. [Online]. Available: http://www2.imm.dtu.dk/documents/ftp/tr99/tr05 99.pdf
14. K. G. Vamvoudakis and F. L. Lewis, "Online actor-critic algorithm to solve the continuous-time infinite horizon optimal control problem," Automatica, vol. 46, no. 5, pp. 878-888, May 2010.
15. D. Vrabie, K. Vamvoudakis, and F. Lewis, "Adaptive optimal controllers based on generalized policy iteration in a continuous-time framework," Med: 2009 17th Mediterranean Conference On Control & Automation, Vols 1-3, pp. 1402-1409, 2009.