Reinforcement Learning
Webpage for the RL course of the Master in Artificial Intelligence (Spring 2026).Webpage for previous editions of the course with name ATCI is available here (it includes some old videos that can help in some topics).
Slides of Lectures:
- Course Information: Presentation and description of the course (updated 11/02/2026)
- Slides for Week 1: Definition of the RL framework. Key elements in RL. Finding the optimal policy using Policy Iteration (updated 11/02/2026)
- Slides for Week 2: Introduction to Model-Free approaches. Monte-Carlo, Q-learning, TD(lambda) (updated 11/02/2026)
- Slides for Week 3 and 4: Function approximation and DQN (updated 11/02/2026)
- Slides for Week 5: Policy gradient methods (updated 11/02/2026)
- Slides for Week 6: Modeling Rewards: and Inverse Reinforcement Learning (IRL)
- Slides for Week 7: MultiAgent Reinforcement Learning (MARL) and 8 : Zero-sum games
- Slides for Week 9: Sample Efficiency I: Model Based Reinforcement Learning (MBRL)
- Slides for Week 10: Sample Efficiency II: Exploration, Conditioned policies and Curriculum Learning
- Slides for Week 11: Extended RL, AGI and applications
Other resources:
- My Mindmap of RL algorithms
Notebooks and software (in construction):
- Notebook 1: Policy evaluation
- Notebook 2: Policy iteration and Value Iteration
- Notebook 3: Monte Carlo on grid-world
- Notebook 4: Introduction to OpenAI and Q-learning and Google colab version(updated 16/2/24)
- Notebook 5: DQN on Lunar Lander (colab version)
- Notebook 6: PQN on Pong Atari Game (colab version)
- Notebook 7: Actor Critic RL (soon to appear)
Additional links [Note that slides have also embedded links to main references!]
- THE book for Reinforcement Learning:
- Richard S. Sutton and Andrew G. Barto. Reinforcement Learning: An Introduction 2nd Edition, 2018 - Blog summary of Reinforcement Learning
- Nice blog description of Gradient methods
Additional Recent bibliography (with links to implementations)
Miguel Morales. Grokking Deep Reinforcement Learning. MANNING, 2020. [http] Alexander Zai and Brandon Brown. Deep Reinforcement Learning in Action. MANNING, 2020. [http] Maxim Lapan. Deep Reinforcement Learning Hands-on. Packt Publishing Ltd., 2nd edition, 2020. [http]
