ACCELERATING PROCEDURES OF THE VALUE-ITERATION ALGORITHM FOR DISCOUNTED MARKOV DECISION-PROCESSES, BASED ON A ONE-STEP LOOKAHEAD ANALYSIS
成果类型：
Article
署名作者：
HERZBERG, M; YECHIALI, U
署名单位：
Tel Aviv University
刊物名称：
OPERATIONS RESEARCH
ISSN/ISSBN：
0030-364X
DOI：
10.1287/opre.42.5.940
发表日期：
1994
页码：
940-946
关键词：
摘要：
Accelerating procedures for solving discounted Markov decision processes problems are developed based on a one-step lookahead analysis of the value iteration algorithm. We apply the criteria of minimum difference and minimum variance to obtain good adaptive relaxation factors that speed up the convergence of the algorithm. Several problems (including Howard's automobile replacement) are tested and a preliminary numerical evaluation reveals considerable reductions in computation time when compared to existing value iteration schemes.