Title
Asynchronous value iteration for markov decision processes with continuous state spaces
Abstract
ABSTRACTWe propose a simulation-based value iteration algorithm for approximately solving infinite horizon discounted MDPs with continuous state spaces and finite actions. At each time step, the algorithm employs the shrinking ball method to estimate the value function at sampled states and uses historical estimates in an interpolation-based fitting strategy to build an approximator of the optimal value function. Under moderate conditions, we prove that the sequence of approximators generated by the algorithm converges uniformly to the optimal value function with probability one. Simple numerical examples are provided to compare our algorithm with two other existing methods.
Year
DOI
Venue
2020
10.5555/3466184.3466513
Winter Simulation Conference
DocType
Citations 
PageRank 
Conference
0
0.34
References 
Authors
0
4
Name
Order
Citations
PageRank
Xiangyu Yang100.34
Jian-Qiang Hu2256.52
Jiaqiao Hu300.34
Yijie Peng43212.59