Markov Decision Process (MDP)
The Markov Decision Process (MDP) is a mathematical framework used to model decision-making in stochastic environments. It plays a crucial role in reinforcement learning (RL), robotics, and optimization problems, helping AI systems make sequential decisions under uncertainty. MDP consists of states, actions, transition probabilities, rewards, and policies, enabling AI models to evaluate and choose the ...