Book_ReinforcementLearning

Project information

This book provides a clear and accessible introduction to Reinforcement Learning (RL), a branch of artificial intelligence focused on how agents learn to make decisions through interaction and feedback from their environment. Aimed at students and beginners in data science, machine learning, and engineering, it presents the fundamental principles behind learning from experience, emphasizing intuition, clarity, and applied understanding.

Combining applied knowledge with well-established academic literature, the text introduces the essential logic of RL without excessive mathematical formality. It helps readers grasp how algorithms balance exploration and exploitation, evaluate rewards, and learn optimal strategies to achieve long-term goals.

data science