Practical reinforcement learning using representation learning and safe exploration for large scale Markov decision processes
作者： Alborz Geramifard
DOI:
关键词:
摘要:
参考文章(102)
Steffen Udluft, Daniel Schneegaß, Anton Maximilian Schäfer, Alexander Hans, Safe exploration for reinforcement learning. the european symposium on artificial neural networks. pp. 143- 148 ,(2008)
Robert Givan, Jia-Hong Wu, Discovering relational domain features for probabilistic planning international conference on automated planning and scheduling. pp. 344- 351 ,(2007)
Stuart I. Reynolds, Adaptive Resolution Model-Free Reinforcement Learning: Decision Boundary Partitioning international conference on machine learning. pp. 783- 790 ,(2000)
Stephen Lin, Robert Wright, Evolutionary tile coding: an automated state abstraction algorithm for reinforcement learning national conference on artificial intelligence. pp. 42- 47 ,(2010)
Lihong Li, Jason D. Williams, Suhrid Balakrishnan, Reinforcement learning for dialog management using least-squares Policy iteration and fast feature selection. conference of the international speech communication association. pp. 2475- 2478 ,(2009)
Manuela M. Veloso, William T. B. Uther, Tree based discretization for continuous state space reinforcement learning national conference on artificial intelligence. pp. 769- 774 ,(1998)
L. Xu, U. Ozguner, Battle management for unmanned aerial vehicles conference on decision and control. ,vol. 4, pp. 3585- 3590 ,(2003) , 10.1109/CDC.2003.1271704
Jonathan P Alighanbari, Mehdi, How, Eric Feron, Task assignment algorithms for teams of UAVs in dynamic environments Massachusetts Institute of Technology. ,(2004)
Richard S. Sutton, Steven D. Whitehead, Online learning with random representations international conference on machine learning. pp. 314- 321 ,(1993) , 10.1016/B978-1-55860-307-3.50047-2
Michael Buro, From Simple Features to Sophisticated Evaluation Functions annual conference on computers. pp. 126- 145 ,(1998) , 10.1007/3-540-48957-6_8