Markov Decision Process

A Markov Decision Process (MDP) is a mathematical framework used for modeling decision-making in environments where outcomes are partly random and partly under the control of a decision-maker.

🔑 Key Components:

• States: Set of possible configurations of the environment.
• Actions: Choices available to the agent.
• Transition Probabilities: Probability of moving to a new state.
• Rewards: Feedback provided after transitions.
• Policy: Strategy for selecting actions in states.