Markov decision process (MDP), also called a stochastic dynamic program or stochastic control problem, is a model for sequential decision making when outcomes are uncertain.[1]
Originating from operations research in the 1950s,[2][3] MDPs have since gained recognition in a variety of fields, including robotics, ecology, economics, healthcare, telecommunications and artificial intelligence.