What is Markov decision process in reinforcement learning?
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19 May 2004 15 Citations | In this study, we propose Markov decision processes as an alternative to the action cost functions approach. |
27 Aug 2005 23 Citations | Also designed is a novel interpretation of Markov decision process providing clear mathematical formulation to connect reinforcement learning as well as to express integrated agent system. |
12 Dec 2000 29 Citations | We propose a simulation-based algorithm for learning good policies for a Markov decision process with unknown transition law, with aggregated states. |
01 Dec 2014 31 Citations | Third, it provides applications to control of partially observable Markov decision processes and, in particular, to Markov decision models with incomplete information. |
| Hence, Bayesian reinforcement learning distinguishes itself from other forms of reinforcement learning by explicitly maintaining a distribution over various quantities such as the parameters of the model, the value function, the policy or its gradient. |
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