Discounted Approximations for Risk-Sensitive Average Criteria in Markov Decision Chains with Finite State Space
From MaRDI portal
Publication:3169133
DOI10.1287/moor.1100.0476zbMath1222.90075OpenAlexW2161423588MaRDI QIDQ3169133
Daniel Hernández-Hernández, Rolando Cavazos-Cadena
Publication date: 27 April 2011
Published in: Mathematics of Operations Research (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1287/moor.1100.0476
Discrete-time Markov processes on general state spaces (60J05) Dynamic programming (90C39) Markov and semi-Markov decision processes (90C40) Probabilistic measure theory (60A10)
Related Items (15)
Risk-sensitive continuous-time Markov decision processes with unbounded rates and Borel spaces ⋮ Average cost criterion induced by the regular utility function for continuous-time Markov decision processes ⋮ Continuous-time Markov decision processes under the risk-sensitive average cost criterion ⋮ Markov decision processes under risk sensitivity: a discount vanishing approach ⋮ Zero-sum risk-sensitive stochastic games on a countable state space ⋮ Risk-sensitive control for a class of nonlinear systems with multiplicative noise ⋮ Risk-sensitive average continuous-time Markov decision processes with unbounded rates ⋮ Time-inconsistent risk-sensitive equilibrium for countable-stated Markov decision processes ⋮ Continuous-time Markov decision processes with risk-sensitive finite-horizon cost criterion ⋮ Risk-sensitive average equilibria for discrete-time stochastic games ⋮ Zero-sum risk-sensitive stochastic games ⋮ Nonzero-Sum Risk-Sensitive Stochastic Games on a Countable State Space ⋮ Risk-Sensitive Discounted Continuous-Time Markov Decision Processes with Unbounded Rates ⋮ Risk-sensitive average continuous-time Markov decision processes with unbounded transition and cost rates ⋮ Risk-averse autonomous systems: a brief history and recent developments from the perspective of optimal control
This page was built for publication: Discounted Approximations for Risk-Sensitive Average Criteria in Markov Decision Chains with Finite State Space
