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Mon. 8/26 |
Course Overview |
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HW 0: Math Self Diagnostic
Prog 0: Tutorial
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2 |
Wed. 8/28 |
Introduction to AI |
PDF |
Closed Captioning Terminator Vision Stuffed Animal Vision Robot Soccer 1 Robot Soccer 2 Google Car Laundry Petman Stapler Fetcher Pacman Demo
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Ch 1, 2 |
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3 |
Fri. 8/30 |
Uninformed Search |
PDF |
Reflex Agent
Odd Reflex Agent
Mastermind Agent
Replanning Agent
DFS Empty Maze
BFS Empty Maze
DFS Water Maze
BFS Water Maze
UCS Empty Maze
DFS Varying Water Maze
BFS Varying Water Maze
UCS Varying Water Maze
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Ch 3.1-3.4 |
HW 1: Search
Prog 1: Search
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Mon. 9/2 |
NO CLASS - Labor Day Holiday |
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4 |
Wed. 9/4 |
Informed Search |
PDF |
UCS Empty Maze
UCS Pacman Small Maze
Greedy Empty Maze
Greedy Pacman Small Maze
A* Pacman Small Maze
Guess the Algorithm!
Guess the Algorithm!
Guess the Algorithm!
Guess the Algorithm!
Guess the Algorithm!
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Ch 3.5-3.6 |
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5 |
Fri. 9/6 |
Constraint Satisfaction Problems (CSPs) |
PDF |
DFS Coloring
Backtracking Coloring
Backtracking with Forward Checking Coloring
Arc Consistency, n-Queens
Backtracking with Forward Checking Coloring - Complex Graph
Backtracking with Arc Consistency Coloring - Complex Graph
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Ch 6.1 |
HW 2: Constraint Satisfaction Problems
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6 |
Mon. 9/9 |
CSPs II |
PDF |
Iterative Improvement - N Queens
Iterative Improvement - Coloring
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Ch 6.2-6.5 |
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7 |
Wed. 9/11 |
Adversarial Search |
PDF |
Mystery Pacman
Depth Limited - d=2
Depth Limited - d=10
Thrashing
Thrashing Fixed
Smart Ghosts Coordinating
Smart Ghosts Coordinating (Zoomed In)
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Ch 5.2-5.5 |
HW 3: Games
Prog 2: Multi-Agent Search
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8 |
Fri. 9/13 |
Expectimax and Utilitites |
PDF |
Minimax vs Expectimax (Min)
Minimax vs Expectimax (Exp)
Adversarial Ghost, Expectimax Pacman
Adversarial Ghost, Minimax Pacman
Random Ghost, Expectimax Pacman
Random Ghost, Minimax Pacman
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Ch 16.1-16.3 |
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9 |
Mon. 9/16 |
Expectimax and Utilitites |
PDF |
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Ch 5.5-5.8 |
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10 |
Wed. 9/18 |
MDPs I |
PDF |
Gridworld |
Ch 17.1-17.3 |
HW 4: Markov Decision Processes
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Fri. 9/20 |
NO CLASS - Industry Advisory Board Meeting |
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11 |
Mon. 9/23 |
MDPs I |
PDF |
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Ch 17.1-17.3 |
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12 |
Wed. 9/25 |
MDPs II |
PDF |
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Ch 17.1-17.3 |
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13 |
Fri. 9/27 |
Reinforcement Learning (RL) |
PDF |
AIBO Walk - Initial
AIBO Walk - Training
AIBO Walk - Finished
Toddler Walk
Crawler
Q-Learning, Gridworld
Q-Learning, Crawler
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Ch 21 |
HW 5: Reinforcement Learning
Prog 3: Reinforcement Learning
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14 |
Mon. 9/30 |
RL II |
PDF |
Q-Learning Auto, Cliff Grid
Q-Learning Manual, Bridge Grid
Q-Learning Epsilon-Greedy, Crawler
Q-Learning Exploration Function, Crawler
Q-Learning, Tiny Pacman
Q-Learning, Trained Pacman
Q-Learning, Tricky Pacman
Approximate Q-Learning, Pacman
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Ch 21 |
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Wed. 10/2 |
Review for Exam I |
PDF |
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Paper
Presentation
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Fri. 10/4 |
Exam I |
Equations |
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Mon. 10/7 |
Go over exam |
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15 |
Wed. 10/9 |
Probability
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PDF |
Ghostbusters, no probability
Ghostbusters, with probability |
Ch. 13.1-13.5 |
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16 |
Fri. 10/11 |
Probability |
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17 |
Mon. 10/14 |
Bayes Nets: Representation |
PDF |
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Ch. 14.1-14.2, 14.4 |
HW 6: Bayes Nets: Representation and Independence |
18 |
Wed. 10/16 |
Bayes Nets: Representation |
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19 |
Fri. 10/18 |
Bayes Nets: Independence |
PDF |
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Ch. 14.3 |
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20 |
Mon. 10/21 |
Bayes Nets: Inference |
PDF |
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Ch. 14.4 |
HW 7: Bayes Nets: Inference and Sampling |
21 |
Wed. 10/23 |
Bayes Nets: Sampling |
PDF |
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Ch. 14.4-14.5 |
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22 |
Fri. 10/25 |
Decision Networks and VPI |
PDF |
Ghostbusters, Probability
Ghostbusters, VPI
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Ch. 16.5-16.6 |
HW 8: VPI and Hidden Markov Models |
23 |
Mon. 10/28 |
Hidden Markov Models (HMMs) |
PDF |
Pacman Sonar - No Beliefs
Ghostbusters, Basic Dynamics
Ghostbusters, Circular Dynamics
Ghostbusters, Whirlpool (Center) Dynamics
Ghostbusters, Circular Dynamics
Pacman Sonar - With Beliefs
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Ch. 15.2, 15.5 |
Prog 4: Ghostbusters |
24 |
Wed. 10/30 |
Particle Filtering and HMMs |
PDF |
Ghostbusters, Exact Filtering
Ghostbusters, Particle Filtering, Moderate Number Particles
Ghostbusters, Particle Filtering, Huge Number Particles
Ghostbusters, Particle Filtering, One Particle
Robot Localization, Sonar
SLAM Mapping
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Ch. 15.2, 15.6 |
ofHMMs HW 9: Particle Filtering and Naive Bayes
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25 |
Fri. 11/1 |
Naive Bayes |
PDF Exam Outline |
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Ch. 20.1-20.2.2 |
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Mon. 11/4 |
Midterm II |
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26 |
Wed. 11/6 |
Perceptrons and Logistic Regression |
PDF |
Multiclass Perceptron
Pacman Apprentice
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Ch. 18.6.3 |
HW 10: Perceptrons
Prog 5: Machine Learning |
27 |
Fri. 11/8 |
Optimization and Neural Networks |
PDF |
Tensorflow Playground |
Ch. 18.8 |
HW 11: Gradient Descent and Neural Networks |
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Mon. 11/11 |
NO CLASS - Veteran's Day Holiday |
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28 |
Wed. 11/13 |
Neural Networks and Decision Trees |
PDF |
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29 |
Fri. 11/15 |
Dalton Caron - Neural Networks |
PDF |
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30 |
Mon. 11/18 |
Mariia Korol - Natural Language Processing |
PDF |
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31 |
Wed. 11/20 |
Eli Hodges - Genetic Algorithms |
PDF |
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32 |
Fri. 11/22 |
Jacob Vesco - Computer Vision |
PDF |
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33 |
Mon. 11/25 |
Blaine Berrington - AI in Chemistry |
PDF |
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Wed. 11/27 |
NO CLASS - Thanksgiving Holidy |
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Fri. 11/29 |
NO CLASS - Thanksgiving Holiday |
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34 |
Mon. 12/2 |
Philosophical Issues and Future Directions
Review for Final Exam |
PDF |
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35 |
Wed. 12/4 |
Burak Adam - Moravec's Paradox |
PDF |
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Fri. 12/6 |
Greg Marlowe - Robotics |
PDF |
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Fri. 12/13 11:30-1:30 |
Final Exam |
PDF |
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