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Blank Slides (with blank pages for quiz questions): Part 1, Part 2, Part 3, Part 4,
Annotated Slides: Part 1, Part 2, Part 3, Part 4,
A slightly different tie-breaking rule is used when inserting the an existing node (state) into a priority queue this year (different from the previous years).
Image by DeepNorth via Wikipedia
Lecture 17 Part 2 (Breadth First Search): Link
Lecture 17 Part 3 (Depth First Search): Link
Lecture 18 Part 1 (Informed Search): Link
Lecture 18 Part 2 (Uniform Cost and Greedy): Link
Lecture 18 Part 3 (A Search): Link
Lecture 20 Part 1 (Hill Climbing): Link
Lecture 20 Part 2 (Simulated Annealing): Link
Lecture 20 Part 3 (Genetic Algorithm): Link
Sliding Puzzle: Link
Water Jugs: Link
All Search: Link
Google Map: Link
Robot Arm: (Game) Link, (2D) Link 2, (3D) Link 3
Professor Jerry Zhu's Slides (with Proofs etc): Link
Simulated Annealing Map: Link
SAT Solver: Link
Genetic Walkers: Link
Genetic Cars: Link
Genetic Eater: Link
Genetic Image: Link
How to get expansion path for DFS? Link
How to get expansion path for IDS? Link
How to get expansion path for UCS? Link
How to get expansion path for BFGS? Link
How to get expansion path for A? Link
How to get expansion path for A*? Link
How to check if a heuristic is admissible? Link
How to find reproduction probabilities? Link
How to solve the lions game? Link
How to solve the pirate game? Link
How to solve the wage competition game (sequential version)? Link
# Summary
📗 Tuesday to Friday lectures: 1:00 to 2:15, Zoom Link
📗 Saturday review sessions: 5:30 to 8:30, Zoom Link
📗 Personal meeting room: always open, Zoom Link
📗 Quiz (use your wisc ID to log in (without "@wisc.edu")): Socrative Link
📗 Math Homework:
M9,
M10,
📗 Programming Homework:
P5,
📗 Examples and Quizzes:
Q17,
Q18,
Q19,
Q20,
# Lectures
📗 Slides (before lecture, usually updated on Sunday):
Blank Slides:
Part 1,
Part 2,
Part 3,
Part 4,
Blank Slides (with blank pages for quiz questions): Part 1, Part 2, Part 3, Part 4,
📗 Slides (after lecture, usually updated on Friday):
Blank Slides with Quiz Questions:
Part 1,
Part 2,
Part 3,
Part 4,
Annotated Slides: Part 1, Part 2, Part 3, Part 4,
📗 Review Session:
PDF. 📗 My handwriting is really bad, you should copy down your notes from the lecture videos instead of using these.
📗 Notes
Lectures 19 and 20 are combined into one single Lecture 20. A slightly different tie-breaking rule is used when inserting the an existing node (state) into a priority queue this year (different from the previous years).
Image by DeepNorth via Wikipedia
# Other Materials
📗 Pre-recorded Videos from 2020
Lecture 17 Part 1 (Uninformed Search): Link Lecture 17 Part 2 (Breadth First Search): Link
Lecture 17 Part 3 (Depth First Search): Link
Lecture 18 Part 1 (Informed Search): Link
Lecture 18 Part 2 (Uniform Cost and Greedy): Link
Lecture 18 Part 3 (A Search): Link
Lecture 20 Part 1 (Hill Climbing): Link
Lecture 20 Part 2 (Simulated Annealing): Link
Lecture 20 Part 3 (Genetic Algorithm): Link
📗 Relevant websites
Sheep Game: Link Sliding Puzzle: Link
Water Jugs: Link
All Search: Link
Google Map: Link
Robot Arm: (Game) Link, (2D) Link 2, (3D) Link 3
Professor Jerry Zhu's Slides (with Proofs etc): Link
Simulated Annealing Map: Link
SAT Solver: Link
Genetic Walkers: Link
Genetic Cars: Link
Genetic Eater: Link
Genetic Image: Link
📗 YouTube videos from 2019 and 2020
How to get expansion path for BFS? Link How to get expansion path for DFS? Link
How to get expansion path for IDS? Link
How to get expansion path for UCS? Link
How to get expansion path for BFGS? Link
How to get expansion path for A? Link
How to get expansion path for A*? Link
How to check if a heuristic is admissible? Link
How to find reproduction probabilities? Link
How to solve the lions game? Link
How to solve the pirate game? Link
How to solve the wage competition game (sequential version)? Link
# Keywords and Notations
📗 Local Search
📗 Hill Climbing (Valley Finding), probability of moving from \(s\) to a state \(s'\) \(p = 0\) if \(f\left(s'\right) \geq f\left(s\right)\) and \(p = 1\) if \(f\left(s'\right) < f\left(s\right)\), where \(f\left(s\right)\) is the cost of the state \(s\).
📗 Simulated Annealing, probability of moving from \(s\) to a worse state \(s'\) = \(p = e^{- \dfrac{\left| f\left(s'\right) - f\left(s\right) \right|}{T\left(t\right)}}\) if \(f\left(s'\right) \geq f\left(s\right)\) and \(p = 1\) if \(f\left(s'\right) < f\left(s\right)\), where \(T\left(t\right)\) is the temperature as time \(t\).
📗 Genetic Algorithm, probability of get selected as a parent in cross-over: \(p_{i} = \dfrac{F\left(s_{i}\right)}{\displaystyle\sum_{j=1}^{n} F\left(s_{j}\right)}\), \(i = 1, 2, ..., N\), where \(F\left(s\right)\) is the fitness of state \(s\).
📗 Adversarial Search
📗 Sequential Game (Alpha Beta Pruning): prune the tree if \(\alpha \geq \beta\), where \(\alpha\) is the current value of the MAX player and \(\beta\) is the current value of the MIN player.
📗 Simultaneous Move Game (rationalizable): remove an action \(s_{i}\) of player \(i\) if it is strictly dominated \(F\left(s_{i}, s_{-i}\right) < F\left(s'_{i}, s_{-i}\right)\), for some \(s'_{i}\) of player \(i\) and for all \(s_{-i}\) of the other players.
📗 Simultaneous Move Game (Nash equilibrium): \(\left(s_{i}, s_{-i}\right)\) is a (pure strategy) Nash equilibrium if \(F\left(s_{i}, s_{-i}\right) \geq F\left(s'_{i}, s_{-i}\right)\) and \(F\left(s_{i}, s_{-i}\right) \geq F\left(s_{i}, s'_{-i}\right)\), for all \(s'_{i}, s'_{-i}\).
Last Updated: November 03, 2025 at 1:02 PM