TITLE:
Conditional Value-at-Risk for Random Immediate Reward Variables in Markov Decision Processes
AUTHORS:
Masayuki Kageyama, Takayuki Fujii, Koji Kanefuji, Hiroe Tsubaki
KEYWORDS:
Markov Decision Processes, Conditional Value-at-Risk, Risk Optimal Policy, Inventory Model
JOURNAL NAME:
American Journal of Computational Mathematics,
Vol.1 No.3,
September
19,
2011
ABSTRACT: We consider risk minimization problems for Markov decision processes. From a standpoint of making the risk of random reward variable at each time as small as possible, a risk measure is introduced using conditional value-at-risk for random immediate reward variables in Markov decision processes, under whose risk measure criteria the risk-optimal policies are characterized by the optimality equations for the discounted or average case. As an application, the inventory models are considered.