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What is Understanding Markov Decision Processes about?
A Markov Decision Process (MDP) is a mathematical framework for modeling decision-making in dynamic systems where outcomes are influenced by randomness or decisions. It consists of elements such as states, actions, rewards, and policies, with the Markov Property indicating that future states depend only on the current state and action taken. This property simplifies decision-making and is foundational for reinforcement learning problems that can be modeled as MDPs.
- Author
- zaurezsakheebbode
- Language
- EN