Reinforcement Learning | David Silver | Course

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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