A framework and a mean-field algorithm for the local control of spatial processes

DOI10.1016/j.ijar.2011.09.007zbMath1242.90284OpenAlexW2100514244WikidataQ60558405 ScholiaQ60558405MaRDI QIDQ433494

Nicklas Forsell, Nathalie Peyrard, Régis Sabbadin

Publication date: 5 July 2012

Published in: International Journal of Approximate Reasoning (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ijar.2011.09.007

zbMATH Keywords

approximate linear programmingapproximate policy iterationdecision-theoretic planningfactored Markov decision processesmean-field principle

Mathematics Subject Classification ID

Decision theory (91B06) Markov and semi-Markov decision processes (90C40)

Related Items (1)

Efficient approximate linear programming for factored MDPs

Cites Work

• Management of the risk of wind damage in forestry: a graph-based Markov decision process approach
• Control of spatially structured random processes and random fields with applications.
• Optimal control of diffusion processes with reflection
• A computational theory of decision networks
• Stochastic dynamic programming with factored representations
• The Linear Programming Approach to Approximate Dynamic Programming
• On Constraint Sampling in the Linear Programming Approach to Approximate Dynamic Programming
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