Decoding the Stochastic Theory in Reinforcement Learning: A Deep Dive into Markov Decision Processes

The article Towards Data Science by Shailey Dash explores the Markov Decision Process (MDP), which forms the theoretical foundation of reinforcement learning problems. It delves into the stochastic theory underlying MDPs, which is crucial for understanding reinforcement learning (RL) in both theory and practice. Understanding the Markov Decision Model in […]