Reinforcement Learning for Pacman

Introduction to Reinforcement Learning: Key Concepts and Applications

Introduces reinforcement learning, covering its definitions, applications, and theoretical foundations, while outlining the course structure and objectives.

Reinforcement Learning: Basics and Applications

Covers the basics of reinforcement learning, including Markov Decision Processes and policy gradient methods, and explores real-world applications and recent advances.

Markov Decision Processes: Foundations of Reinforcement Learning

Covers Markov Decision Processes, their structure, and their role in reinforcement learning.

Reinforcement Learning for Pacman

Explores applying reinforcement learning to teach Pacman to play autonomously using policy gradient methods and Markov decision processes.

Interactive Lecture: Reinforcement Learning

Explores advanced reinforcement learning topics, including policies, value functions, Bellman recursion, and on-policy TD control.