BOUNDED-PARAMETER PARTIALLY OBSERVABLE MARKOV DECISION PROCESSES: FRAMEWORK AND ALGORITHM

DOI10.1142/S0218488513500396zbMath1321.91027OpenAlexW2118538898MaRDI QIDQ2948867

Yaodong Ni, Zhi-Qiang Liu

Publication date: 6 October 2015

Published in: International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1142/s0218488513500396

zbMATH Keywords

decision making under uncertaintyplanning under uncertaintybounded-parameter POMDPmodified value iterationULVI algorithm

Mathematics Subject Classification ID

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

Related Items (1)

A survey of decision making and optimization under uncertainty

Cites Work

• Planning and acting in partially observable stochastic domains
• Efficient solutions to factored MDPs with imprecise transition probabilities
• Partially observable Markov decision processes with imprecise parameters
• Bounded-parameter Markov decision processes
• Generalizing Markov decision processes to imprecise probabilities
• Policy iteration for bounded-parameter POMDPs
• A survey of algorithmic methods for partially observed Markov decision processes
• Percentile Optimization for Markov Decision Processes with Parameter Uncertainty
• Parameter Imprecision in Finite State, Finite Action Dynamic Programs
• State of the Art—A Survey of Partially Observable Markov Decision Processes: Theory, Models, and Algorithms
• Computationally Feasible Bounds for Partially Observed Markov Decision Processes
• The Optimal Control of Partially Observable Markov Processes over the Infinite Horizon: Discounted Costs
• Markov Decision Processes with Imprecise Transition Probabilities
• The Optimal Control of Partially Observable Markov Processes over a Finite Horizon
• Markovian Decision Processes with Uncertain Transition Probabilities

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