Mathematical principles of reinforcement

The mathematical principles of reinforcement primarily relate to the field of reinforcement learning (RL), which is a subset of machine learning. Reinforcement learning focuses on how agents should take actions in an environment to maximize some notion of cumulative reward. Here are some key concepts and principles related to the mathematics of reinforcement learning: 1. **Agent, Environment, and Rewards**: - **Agent**: The learner or decision maker. - **Environment**: Everything the agent interacts with.