Most of the slides for the classes I teach, both graduate and undergraduate, are supposed to be here.  These are pools of slides; for each class and each level (graduate/undergrad) I decide which material is covered and which material is skipped. In other words, there is  often more in these slides than the material that is covered in class. Yet, take a look, it won´t hurt. Also, some slides (most in the second part below are not available here yet )

A. Modeling and Problem Solving (normally covered in AI 1 )

• Search
• Logic and SAT
• Classical Planning and Search
• Other Approaches in Classical Planning
• Planning and Control:  Uncertainty and Feedback,  MDPs,  DP
• Constraints
• Scheduling, Temporal Planning

• Probabilistic Reasoning
• Bayesian Networks
• Decision Theory and Influence Diagrams
• Sequential Decision Making; Reinforcement learning
• Statistical Pattern Recognition 1, 2
• Neural Networks