Brief information

• Instructor: David Silver
• Course homepage: [LINK]
• Video lecture list: [LINK]

Lecture schedule

• Lecture 1: Introduction to Reinforcement Learning
• Lecture 2: Markov Decision Processes
• Lecture 3: Planning by Dynamic Programming
• Lecture 4: Model-Free Prediction
• Lecture 5: Model-Free Control
• Lecture 6: Value Function Approximation
• Lecture 7: Policy Gradient Methods
• Lecture 8: Integrating Learning and Planning
• Lecture 9: Exploration and Exploitation
• Lecture 10: Case Study: RL in Classic Games

My summary

• Lecture 1: Introduction to Reinforcement Learning [LINK]
• Lecture 2: Markov Decision Processes?[LINK]
• Lecture 3: Planning by Dynamic Programming?[LINK]
• Lecture 4: Model-Free Prediction?[LINK]
• Lecture 5: Model-Free Control?[LINK]
• Lecture 6: Value Function Approximation?[LINK]
• Lecture 7: Policy Gradient Methods?[LINK]
• Lecture 8: Integrating Learning and Planning?[LINK]
• Lecture 9: Exploration and Exploitation?[LINK]
• Lecture 10: Case Study: RL in Classic Games?[LINK]

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