Principles of Reinforcement Learning: An Introduction with Python
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Reinforcement Learning (RL) is a type of machine learning. It trains an agent to make decisions by interacting with an environment. This article covers the basic concepts of RL. These include states, actions, rewards, policies, and the Markov Decision Process (MDP). By the end, you will understand how RL works. You will also learn how to implement it in Python.
Key Concepts in Reinforcement Learning
Reinforcement Learning (RL) involves several core ideas that shape how machines learn from experience and make decisions:
- Agent: It’s the decision-maker that interacts with its environment.
- Environment: The external system with