An online actor-critic algorithm with function approximation for constrained Markov decision processes

DOI10.1007/s10957-012-9989-5zbMath1262.90189OpenAlexW2073314543MaRDI QIDQ438776

J. Herrera, H. S. Yoon

Publication date: 31 July 2012

Published in: Journal of Optimization Theory and Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10957-012-9989-5

zbMATH Keywords

function approximationactor critic algorithmconstrained Markov decision processlong-run average cost criterion

Mathematics Subject Classification ID

Markov chains (discrete-time Markov processes on discrete state spaces) (60J10) Markov and semi-Markov decision processes (90C40)

Related Items

Event-based optimization approach for solving stochastic decision problems with probabilistic constraint, Multiscale Q-learning with linear function approximation, Queueing Network Controls via Deep Reinforcement Learning, Suboptimal control for nonlinear systems with disturbance via integral sliding mode control and policy iteration, Variance-constrained actor-critic algorithms for discounted and average reward MDPs, Optimal deterministic controller synthesis from steady-state distributions, Risk-Constrained Reinforcement Learning with Percentile Risk Criteria

Cites Work

• The Borkar-Meyn theorem for asynchronous stochastic approximations
• An actor-critic algorithm with function approximation for discounted cost constrained Markov decision processes
• Natural actor-critic algorithms
• Average cost temporal-difference learning
• An actor-critic algorithm for constrained Markov decision processes
• Optimal flow control of a class of queueing networks in equilibrium
• Multivariate stochastic approximation using a simultaneous perturbation gradient approximation
• Asynchronous Stochastic Approximations
• OnActor-Critic Algorithms
• Simulation-based optimization of Markov reward processes
• The O.D.E. Method for Convergence of Stochastic Approximation and Reinforcement Learning
• Perturbation theory and finite Markov chains
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item