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An actor-critic algorithm for constrained Markov decision processes
Authors:VS Borkar  
Affiliation:School of Technology and Computer Science, Tata Institute of Fundamental Research, Homi Bhabha Road, Mumbai 400005, India
Abstract:An actor-critic type reinforcement learning algorithm is proposed and analyzed for constrained controlled Markov decision processes. The analysis uses multiscale stochastic approximation theory and the envelope theorem' of mathematical economics.
Keywords:Actor-critic algorithms  Reinforcement learning  Constrained Markov decision processes  Stochastic approximation  Envelope theorem
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