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广义随机最短路径问题的启发式搜索Heuristic Search for Generalized Stochastic Shortest Path MDPs |
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| 课程网址: | http://videolectures.net/icaps2011_kolobov_heuristic/ |
| 主讲教师: | Andrey Kolobov |
| 开课单位: | 华盛顿大学 |
| 开课时间: | 2011-07-21 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | Research in efficient methods for solving infinite-horizon MDPs has so far concentrated primarily on discounted MDPs and the more general stochastic shortest path problems (SSPs). These are MDPs with 1) an optimal value function V* that is the unique solution of Bellman equation and 2) optimal policies that are the greedy policies w.r.t. V*. This paper’s main contribution is the description of a new class of MDPs, that have well-defined optimal solutions that do not comply with either 1 or 2 above. We call our new class Generalized Stochastic Shortest Path (GSSP) problems. GSSP allows more general reward structure than SSP and subsumes several established MDP types including SSP, positive-bounded, negative, and discounted-reward models. While existing efficient heuristic search algorithms like LAO* and LRTDP are not guaranteed to converge to the optimal value function for GSSPs, we present a new heuristic-search-based family of algorithms, FRET (Find, Revise, Eliminate Traps). A preliminary empirical evaluation shows that FRET solves GSSPs much more efficiently than Value Iteration. |
| 关 键 词: | 随机最短路径问题; 最优的解决方案; 启发式搜索算法 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2020-06-27：yumf |
| 阅读次数: | 79 |