## Lecture Slides

NoTopicDateSlides
0Organizational Matters1.3.screen
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1Introduction1.3.screen
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2Introduction: AI Past and Present3.3.screen
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3Introduction: Rational Agents3.3.screen
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4Introduction: Environments and Problem Solving Methods8.3.screen
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5State-Space Search: State Spaces8.3.screen
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6State-Space Search: Representation of State Spaces10.3.screen
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7State-Space Search: Examples of State Spaces10.3.screen
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8State-Space Search: Data Structures for Search Algorithms15.3.screen
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9State-Space Search: Tree Search and Graph Search15.3.screen
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11State-Space Search: Uniform Cost Search17.3.screen
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12State-Space Search: Depth-first Search & Iterative Deepening22.3.screen
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13State-Space Search: Heuristics22.3.screen
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14State-Space Search: Analysis of Heuristics24.3.screen
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15State-Space Search: Best-first Graph Search24.3.screen
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16State-Space Search: Greedy BFS, A*, Weighted A*29.3.screen
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17State-Space Search: IDA*29.3.screen
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18State-Space Search: Properties of A, Part I31.3.screen
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19State-Space Search: Properties of A, Part II31.3.screen
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20Combinatorial Optimization: Introduction and Hill-Climbing7.4.screen
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22Constraint Satisfaction Problems: Introduction and Examples12.4.screen
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23Constraint Satisfaction Problems: Constraint Networks12.4.screen
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24Constraint Satisfaction Problems: Backtracking14.4.screen
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25Constraint Satisfaction Problems: Arc Consistency14.4.screen
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26Constraint Satisfaction Problems: Path Consistency19.4.screen
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27Constraint Satisfaction Problems: Constraint Graphs19.4.screen
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28Constraint Satisfaction Problems: Decomposition Methods21.4.screen
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29Propositional Logic: Basics21.4.screen
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30Propositional Logic: Reasoning and Resolution26.4.screen
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31Propositional Logic: DPLL Algorithm26.4.screen
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32Propositional Logic: Local Search and Outlook28.4.screen
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33Automated Planning: Introduction28.4.screen
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34Automated Planning: Planning Formalisms3.5.screen
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35Automated Planning: Delete Relaxation3.5.screen
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36Automated Planning: Delete Relaxation Heuristics5.5.screen
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37Automated Planning: Abstraction5.5.screen
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38Automated Planning: Landmarks10.5screen
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39Automated Planning: Landmark Heuristics10.5.screen
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40Board Games: Introduction and State of the Art12.5.screen
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41Board Games: Minimax Search and Evaluation Functions12.5.screen
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42Board Games: Alpha-Beta Search17.5.screen
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43Monte-Carlo Tree Search: Introduction17.5.screen
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45AlphaGo and Outlook19.5.screen
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## Exercises

NoDue DateFiles
110.03.21Sheet
217.03.21Sheet
state-spaces.tar.gz
324.03.21Sheet
uniform-cost-search.tar.gz
431.03.21Sheet
astar-search.tar.gz
507.04.21Sheet
614.04.21Sheet
hill-climbing.tar.gz
721.04.21Sheet
828.04.21Sheet
cantons.dot
905.05.21Sheet
1012.05.21Sheet
hamilton-cycle.tar.gz
1119.05.21Sheet
1226.05.21Sheet
1302.06.21Bonus Sheet

## Supplementary Material

Chap.Description
1Turing: "Computation Machinery and Intelligence"
2Bowling et al.: "Heads-up Limit Hold’em Poker is Solved"
2DARPA challenge videos: 1, 2
2Silver et al.: "Mastering the game of Go with deep neural networks and tree search" (*)
68-Puzzle: explicit graph, declarative representation, black box
6Delling et al.: "Engineering Route Planning Algorithms"
8Burns et al.: "Implementing Fast Heuristic Search Code"
10Korf and Schultze: "Large-Scale Parallel Breadth-First Search"
12Complexity estimation script
17Korf: "Depth-First Iterative Deepening: An Optimal Admissible Tree Search" (*)
17Helmert et al.: "Iterative Budgeted Exponential Search"
19Dechter and Pearl: "Generalized Best-First Search Strategies and the Optimality of A*" (*)
20Hill climbing script
21Hill climbing with stagnation script
21Hill climbing with stagnation and random file script
22McGuire et al.: "There is no 16-Clue Sudoku"
22Numberphile video on Four Colour Problem
26Simonis: "Sudoku as a Constraint Problem"
31Davis, Logemann and Loveland: "A Machine Program for Theorem-Proving" (*)
32Katebi et al.: "Empirical Study of the Anatomy of Modern SAT Solvers"
32Bayless et al.: "SAT Modulo Monotonic Theories"
34Blocksworld PDDL model
36Keyder and Geffner: "Heuristics for Planning with Action Costs Revisited"
40Shannon: "Programming a Computer for Playing Chess" (*)
41Giambatista Lolli: "Osservazioni teorico-pratiche sopra il Giuoco degli Scacchi ossia il Giuoco degli scacchi eposta nel suo miglior lume"
42Schaeffer et al.: "Checkers Is Solved" (*)
42Alpha-Beta best-case script
45Silver et al.: "Mastering the game of Go with deep neural networks and tree search" (*)

(*) Please get in touch with us if you are interested in this material. For copyright reasons, we are not allowed to make it available online.