Important Links
Lecture Slides
| No | Topic | Date | Slides |
|---|---|---|---|
| A1 | Organizational Matters | 26.02. | |
| A2 | What is Artificial Intelligence? | 26.02. | |
| A3 | AI Past and Present | 28.02. | |
| A4 | Rational Agents | 28.02. | |
| A5 | Introduction: Environments and Problem Solving Methods | 04.03. | |
| B1 | State-Space Search: State Spaces | 04.03. | |
| B2 | State-Space Search: Representation of State Spaces | 06.03. | |
| B3 | State-Space Search: Examples of State Spaces | 06.03. | |
| B4 | State-Space Search: Data Structures for Search Algorithms | 11.03. | |
| B5 | State-Space Search: Tree Search and Graph Search | 11.03. | |
| B6 | State-Space Search: Breadth-first Search | 13.03. | |
| B7 | State-Space Search: Uniform Cost Search | 13.03. | |
| B8 | State-Space Search: Depth-first Search & Iterative Deepening | 18.03. | |
| B9 | State-Space Search: Heuristics | 18.03. | |
| B10 | State-Space Search: Analysis of Heuristics | 20.03. | |
| B11 | State-Space Search: Best-first Graph Search | 20.03. | |
| B12 | State-Space Search: Greedy BFS, A*, Weighted A∗ | 25.03. | |
| B13 | State-Space Search: IDA∗ | 25.03. | |
| B14 | State-Space Search: Properties of A∗, Part I | 27.03. | |
| B15 | State-Space Search: Properties of A∗, Part II | 27.03. | |
| C1 | Combinatorial Optimization: Introduction and Hill-Climbing | 03.04. | |
| C2 | Combinatorial Optimization: Advanced Techniques | 03.04. | |
| D1 | Constraint Satisfaction Problems: Introduction and Examples | 08.04. | |
| D2 | Constraint Satisfaction Problems: Constraint Networks | 08.04. | |
| D3 | Constraint Satisfaction Problems: Backtracking | 10.04. | |
| D4 | Constraint Satisfaction Problems: Arc Consistency | 10.04. | |
| D5 | Constraint Satisfaction Problems: Path Consistency | 15.04. | |
| D6 | Constraint Satisfaction Problems: Constraint Graphs | 15.04. | |
| D7 | Constraint Satisfaction Problems: Decomposition Methods | 17.04. | |
| E1 | Propositional Logic: Syntax and Semantics | 17.04. | |
| E2 | Propositional Logic: Equivalence and Normal Forms | 22.04. | |
| E3 | Propositional Logic: Reasoning and Resolution | 22.04. | |
| E4 | Propositional Logic: DPLL Algorithm | 24.04. | |
| E5 | Propositional Logic: Local Search and Outlook | 24.04. | |
| F1 | Automated Planning: Introduction | 29.04. | |
| F2 | Automated Planning: Planning Formalisms | 29.04. | |
| F3 | Automated Planning: Delete Relaxation | 06.05. | |
| F4 | Automated Planning: Delete Relaxation Heuristics | 06.05. | |
| F5 | Automated Planning: Abstraction | 08.05. | |
| F6 | Automated Planning: Abstraction Heuristics | 08.05. | |
| G1 | Board Games: Introduction and State of the Art | 13.05. | |
| G2 | Board Games: Minimax Search and Evaluation Functions | 13.05. | |
| G3 | Board Games: Alpha-Beta Search | 15.05. | |
| G4 | Board Games: Stochastic Games | 15.05. | |
| G5 | Board Games: Monte-Carlo Tree Search Framework | 22.05. | |
| G6 | Board Games: Monte-Carlo Tree Search Variants | 22.05. | |
| Complete Slide Set |
Exercises
are provided via ADAM
Supplementary Material
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