Markov decision processes with sequential sensor measurements

DOI10.1016/J.AUTOMATICA.2019.02.026zbMath1421.90159OpenAlexW2920238156WikidataQ128287011 ScholiaQ128287011MaRDI QIDQ1737870

Behçet Açıkmeşe, Dylan Janak, Mahmoud El Chamie

Publication date: 24 April 2019

Published in: Automatica (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.automatica.2019.02.026

zbMATH Keywords

reinforcement learningMarkov decision process (MDP)finite horizon sequentially-observed MDP (SO-MDP)linear programming based synthesissequential sensor measurements

Mathematics Subject Classification ID

Markov and semi-Markov decision processes (90C40)

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Cites Work

• Planning and acting in partially observable stochastic domains
• Continuous-time Markov decision processes. Theory and applications
• Containment control of leader-following multi-agent systems with Markovian switching network topologies and measurement noises
• Convex Necessary and Sufficient Conditions for Density Safety Constraints in Markov Chain Synthesis
• Optimal Statistical Decisions
• Algorithms for Reinforcement Learning
• Dynamic Output-Feedback Control for Singular Markovian Jump System: LMI Approach
• Finite-time analysis of the multiarmed bandit problem
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