Hierarchical Optimization of Policy-Coupled Semi-Markov Decision Processes
暂无分享,去创建一个
[1] Averill M. Law,et al. Simulation Modeling and Analysis , 1982 .
[2] Stanley Gershwin. A hierarchical framework for manufacturing systems scheduling: A two-machine example , 1987, 26th IEEE Conference on Decision and Control.
[3] Stanley B. Gershwin,et al. Simulation experience with a hierarchical scheduling policy for a simple manufacturing system , 1988, Proceedings of the 27th IEEE Conference on Decision and Control.
[4] David L. Woodruff,et al. CONWIP: a pull alternative to kanban , 1990 .
[5] Martin L. Puterman,et al. Markov Decision Processes: Discrete Stochastic Dynamic Programming , 1994 .
[6] Thomas Dean,et al. Decomposition Techniques for Planning in Stochastic Domains , 1995, IJCAI.
[7] Andrew G. Barto,et al. Improving Elevator Performance Using Reinforcement Learning , 1995, NIPS.
[8] Dimitri P. Bertsekas,et al. Reinforcement Learning for Dynamic Channel Allocation in Cellular Telephone Systems , 1996, NIPS.
[9] Asbjoern M. Bonvik,et al. A comparison of production-line control mechanisms , 1997 .
[10] Satinder P. Singh,et al. How to Dynamically Merge Markov Decision Processes , 1997, NIPS.
[11] Stuart J. Russell,et al. Reinforcement Learning with Hierarchies of Machines , 1997, NIPS.
[12] Doina Precup,et al. Multi-time Models for Temporally Abstract Planning , 1997, NIPS.
[13] Doina Precup,et al. Intra-Option Learning about Temporally Abstract Actions , 1998, ICML.
[14] Kee-Eung Kim,et al. Solving Very Large Weakly Coupled Markov Decision Processes , 1998, AAAI/IAAI.
[15] Thomas G. Dietterich. The MAXQ Method for Hierarchical Reinforcement Learning , 1998, ICML.
[16] Ronald Parr,et al. Flexible Decomposition Algorithms for Weakly Coupled Markov Decision Problems , 1998, UAI.