期刊
STOCHASTICS-AN INTERNATIONAL JOURNAL OF PROBABILITY AND STOCHASTIC PROCESSES
卷 86, 期 4, 页码 655-675出版社
TAYLOR & FRANCIS LTD
DOI: 10.1080/17442508.2013.872644
关键词
risk-sensitive control; finite horizon problem; infinite horizon discounted cost; infinite horizon average cost; multiplicative ergodic theorem; HJB equation; Poisson equation; policy improvement algorithm
资金
- SPM fellowship of CSIR
- UGC Centre for Advanced Study
We study risk-sensitive control of continuous time Markov chains taking values in discrete state space. We study both finite and infinite horizon problems. In the finite horizon problem we characterize the value function via Hamilton Jacobi Bellman equation and obtain an optimal Markov control. We do the same for infinite horizon discounted cost case. In the infinite horizon average cost case we establish the existence of an optimal stationary control under certain Lyapunov condition. We also develop a policy iteration algorithm for finding an optimal control.
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