Markov decision processes with risk-sensitive criteria: dynamic programming operators and discounted stochastic games

2003 ◽  
Author(s):  
R. Cavazos-Cadena ◽  
E. Fernandez-Gaucherand
Keyword(s):  
Dynamic Programming ◽  
Markov Decision Processes ◽  
Stochastic Games ◽  
Decision Processes ◽  
Risk Sensitive ◽  
Markov Decision

Cost rate heuristics for semi-Markov decision processes

1992 ◽  
Vol 29 (03) ◽  
pp. 633-644
Author(s):  
K. D. Glazebrook ◽  
Michael P. Bailey ◽  
Lyn R. Whitaker
Keyword(s):  
Dynamic Programming ◽  
Markov Decision Processes ◽  
Preventive Maintenance ◽  
Decision Processes ◽  
Cost Rate ◽  
Backwards Induction ◽  
Optimal Policies ◽  
Markov Decision ◽  
Speed Of Evolution

In response to the computational complexity of the dynamic programming/backwards induction approach to the development of optimal policies for semi-Markov decision processes, we propose a class of heuristics resulting from an inductive process which proceeds forwards in time. These heuristics always choose actions in such a way as to minimize some measure of the current cost rate. We describe a procedure for calculating such cost rate heuristics. The quality of the performance of such policies is related to the speed of evolution (in a cost sense) of the process. A simple model of preventive maintenance is described in detail. Cost rate heuristics for this problem are calculated and assessed computationally.

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