Strategy Complexity of Point Payoff, Mean Payoff and Total Payoff Objectives in Countable MDPs

DOI10.46298/lmcs-19(1:16)2023OpenAlexW4323317293MaRDI QIDQ5883745

Unnamed Author, Richard Mayr

Publication date: 22 March 2023

Published in: Logical Methods in Computer Science (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2203.07079v4

zbMATH Keywords

Markov decision processesmean payoffstrategy complexity

Mathematics Subject Classification ID

Logic in computer science (03B70) Computer science (68-XX)

Cites Work

• Markov decision processes with applications to finance.
• Optimal Markov strategies
• The existence of good Markov strategies for decision processes with general payoffs
• Simplifying optimal strategies in \(\limsup\) and \(\liminf\) stochastic games
• Advances in dynamic games. Applications to economics, finance, optimization and stochastic control.
• Approximating the termination value of one-counter MDPs and stochastic games
• Reachability and safety objectives in Markov decision processes on long but finite horizons
• Recursive Markov Decision Processes and Recursive Stochastic Games
• Qualitative Analysis of VASS-Induced MDPs
• Energy and Mean-Payoff Parity Markov Decision Processes
• A Survey of Stochastic Games with Limsup and Liminf Objectives
• Handbook of Model Checking
• On the Existence of Stationary Optimal Strategies
• A survey of computational complexity results in systems and control
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