About Machine Learning ( Part 10: Reinforcement Learning )
Reinforcement Learning (RL) is an exciting field of machine learning where an agent learns how to behave in an environment in order to maximize cumulative rewards. The foundation of RL lies in Markov Decision Processes (MDPs), which provide a mathematical framework for modeling decision-making scenarios. In this blog, we will explore the core concepts of RL and MDPs, and how they interconnect to help an agent learn optimal behavior.