Markov-achievable payoffs for finite-horizon decision models.

DOI10.1016/S0304-4149(97)00095-1zbMath1099.90588OpenAlexW2080391834MaRDI QIDQ1965904

Xiaobo Wang, Victor C. Pestien

Publication date: 1 March 2000

Published in: Stochastic Processes and their Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/s0304-4149(97)00095-1

zbMATH Keywords

payoff functionMarkov decision modelMarkov plan

Mathematics Subject Classification ID

Dynamic programming (90C39) Stopping times; optimal stopping problems; gambling theory (60G40) Markov renewal processes, semi-Markov processes (60K15) Markov and semi-Markov decision processes (90C40)

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Stationary policies and Markov policies in Borel dynamic programming
• The existence of good Markov strategies for decision processes with general payoffs
• Finite-stage reward functions having the Markov adequacy property
• Markov decision processes: Discounted expected reward or average expected reward?
• Multiplicative Markov Decision Chains
• Controlled Markov Processes with Arbitrary Numerical Criteria
• Constrained Markov Decision Models with Weighted Discounted Rewards
• Memoryless Strategies in Finite-Stage Dynamic Programming
• Discounted Dynamic Programming
• Risk-Sensitive Markov Decision Processes

This page was built for publication: Markov-achievable payoffs for finite-horizon decision models.