Course Material

Software | Lecture Notes | Literature | Tutorials


Lecture Notes

LectureDateTopicCourse Material
102.10.2006 Introduction
209.10.2006 Markov Decision Processes
316.10.2006 Optimal Value Functions
423.10.2006 Dynamic Programming, Monte Carlo Methods
530.10.2006 Temporal Difference Learning
606.11.2006 Eligibility Traces
713.11.2006 Function Approximation
820.11.2006 Model-based RL, Hierarchical RL
927.11.2006 Policy Gradient Methods
1004.12.2006 RL in Robotics, Imitation Learning
1111.12.2006 Biological Hypotheses about RL
1208.01.2007 Genetic Algorithms
1315.01.2007 Advanced Topics in Genetic Algorithms
1422.01.2007 Neuro-Evolution of Augmenting Topologies
1529.01.2007 Written Exam  

Slides from Practicals

110.10.2006 Organisation, First Exercise Sheet
231.10.2006 Solutions of First Exercise Sheet  
307.11.2006 Second Exercise Sheet, Tutorial for RL Toolbox
414.11.2006 Tutorial for RL Toolbox
505.12.2006 Presentation of Projects
609.01.2007 Tutorial for GA Toolbox
723.01.2007 Preparation for MLB Exam

Literature and Slides

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