Value set iteration for Markov decision processes

DOI10.1016/J.AUTOMATICA.2014.05.009zbMath1296.93207OpenAlexW4251216676MaRDI QIDQ459022

Hyeong Soo Chang

Publication date: 8 October 2014

Published in: Automatica (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.automatica.2014.05.009

zbMATH Keywords

dynamic programmingMarkov decision processesconstrained optimizationvalue iteration

Mathematics Subject Classification ID

Dynamic programming in optimal control and differential games (49L20)

Related Items (1)

Value set iteration for two-person zero-sum Markov games

Cites Work

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• Simulation-based algorithms for Markov decision processes
• Policy set iteration for Markov decision processes
• Accelerating the convergence of value iteration by using partial transition functions
• Random Convex Programs
• Approximate Dynamic Programming
• Acceleration Operators in the Value Iteration Algorithms for Markov Decision Processes
• Accelerating Procedures of the Value Iteration Algorithm for Discounted Markov Decision Processes, Based on a One-Step Lookahead Analysis
• Notes on the Scenario Design Approach
• The Scenario Approach to Robust Control Design
• A Stochastic Approximation Framework for a Class of Randomized Optimization Algorithms
• A survey of computational complexity results in systems and control

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