Risk-sensitive optimal control for Markov decision processes with monotone cost

Mathematics of Operations Research

Volumn 27, Issue 1, 2002, Pages 192-209

  Borkar, V S ^a   Meyn, S P ^b  

^a TATA INSTITUTE OF FUNDAMENTAL RESEARCH   (India)

^b University of Illinois at Urbana Champaign   (United States)

Author keywords

Dynamic programming; Optimal control; Risk sensitive control

Indexed keywords

COSTS; DECISION THEORY; FEEDBACK; ITERATIVE METHODS; OPTIMAL CONTROL SYSTEMS; RISKS; STATE SPACE METHODS;

MARKOV DECISION PROCESSES;

MARKOV PROCESSES;

EID: 0036474404     PISSN: 0364765X     EISSN: None     Source Type: Journal    
DOI: 10.1287/moor.27.1.192.334     Document Type: Article

References (23)

1. Multiplicative ergodic theorems and large deviations for an irreducible Markov chain
2. Controlled Markov chains with risk-sensitive criteria: Average cost, optimality equations, and optimal solutions
3. Value iteration and optimization of multiclass queueing networks
4. Risk sensitive control of discrete time partially observed Markov processes with infinite horizon
5. Risk sensitive control of finite state machines on an infinite horizon i
6. Risk sensitive optimal control and differential games
7. A Lyapunov bound for solutions of Poisson's equation
8. Risk sensitive control of Markov processes in countable state space
9. Risk-sensitive Markov decision processes
10. Optimal stochastic linear systems with exponential performance criteria and their relation to deterministic differential games
11. Risk-sensitive control and dynamic games for partially observed discrete-time nonlinear systems
12. Precise limit theorems and multiplicative ergodicity for Markov processes
13. The policy improvement algorithm for Markov decision processes with general state space
14. Algorithms for optimization and stabilization of controlled Markov chains
15. Multiplicative Markov decision chains