Optimal schedulers vs optimal bases: an approach for efficient exact solving of Markov decision processes

DOI10.1016/j.tcs.2013.08.020zbMath1359.68193OpenAlexW2087871167MaRDI QIDQ2453111

Sergio Giro

Publication date: 6 June 2014

Published in: Theoretical Computer Science (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.tcs.2013.08.020

zbMATH Keywords

linear programmingoptimal policiesprobabilistic systemsoptimal basisexact arithmeticoptimal schedulersoptimal adversaries

Mathematics Subject Classification ID

Specification and verification (program logics, model checking, etc.) (68Q60) Probability in computer science (algorithm analysis, random structures, phase transitions, etc.) (68Q87)

Related Items (1)

Interval iteration algorithm for MDPs and IMDPs

Uses Software

• PRISM
• GLPK

Cites Work

• The Simplex and Policy-Iteration Methods Are Strongly Polynomial for the Markov Decision Problem with a Fixed Discount Rate
• Model checking of probabilistic and nondeterministic systems
• Quantitative Multi-objective Verification for Probabilistic Systems
• Fast randomized consensus using shared memory
• Exponential Lower Bounds for Policy Iteration
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