Course Material

Software | Lecture Notes | Literature | Tutorials

Software


Lecture Notes

LectureDateTopicCourse Material
105.10.04 Introduction to Reinforcement Learning Slides from Sutton / Barto:
212.10.04 The Reinforcement Learning Problem Slides from Sutton / Barto:
319.10.04 Theory of Reinforcement Learning 1/2 Theorems (PDF)
402.11.04 Theory of Reinforcement Learning 2/2  
509.11.04 Temporal Difference Learning, Eligibility Traces Slides from Sutton / Barto:
616.11.04 Adaptive Control, Humanoid Robots  
723.11.04 Function Approximation in RL Slides from Sutton / Barto:
830.11.04 Hierarchical Reinforcement Learning Papers:
907.12.04 Policy Gradient RL Papers:
1014.12.04 RL for Motor Control Slides:
1111.01.05 Evolutionary Algorithms  
1218.01.05 Learning and Evolution, GA in nature


Slides from Practicals

LectureDateTopicSlides
108.10.04 Organization, Exploration/Exploitation Dilemma (PDF)
229.10.04 Problem Set 1, Value Functions (PDF)
305.11.04 Tutorial: Reinforcement Learning Tutorial Old Tutorial (PDF)
412.11.04 Presentation Problem Set 1  
526.11.04 Problem Set 2, On- / off-policy Learning, Self-play Learning (PDF)
610.12.04 Problem Set 2, Policy Gradient RL (PDF)
717.12.04 Presentation Problem Set 2  
814.01.05 Genetic Algorithms and Toolbox



Literature and Slides



* Thanks to Prof. Andrew G. Barto for providing his lecture slides.


Tutorials