Markov Decision Processes
Michael Hu
Abstract
Markov decision processes (MDPs) offer a powerful framework for tackling sequential decision-making problems in the presence of uncertainty in reinforcement learning. Their applications span various domains, including robotics, finance, and optimal control.
Topics & Concepts
Markov decision processReinforcement learningArtificial intelligenceComputer scienceMarkov chainMachine learningPartially observable Markov decision processMarkov processControl (management)Markov modelMathematicsStatisticsTransportation and Mobility Innovations