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Outline of Topics
- Overview, agents, environments (Chaps 1 and 2)
- Search (Chaps 3, 4.1, and 5)
- Knowledge representation and logic (Selected topics from Chaps 7-9)
- Uncertainty & Bayesian networks (Selected topics from Chaps 13-15
and 17)
- Machine Learning: Learning from examples (Chap 18)
- Machine Learning: Reinforcement learning (Chap 21)
Midterm Monday, October 28, in class (closed book, except for one 8 1/2'' x 11'' page of notes)
Schedule of Lectures and Readings
Visit here for the schedule of lectures/reading/assignments. We will update it frequently over the quarter.
| Date |
Topic |
Readings |
Slides |
Comments and Assignments |
| Wed, Sep 25 |
Introduction |
AIMA Ch. 1 |
PDF
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Project 0: Python tutorial (no need to turn in) |
| Fri, Sep 27 |
Agents and Environments |
AIMA Ch. 2 |
PDF
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| Mon, Sep 30 |
Search |
AIMA Ch. 3 |
PDF
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Project #1 assigned |
| Wed, Oct 2 |
Informed Search |
AIMA Ch. 3 |
PDF
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| Fri, Oct 4 |
Heuristics |
AIMA Ch. 3 |
PDF
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| Mon, Oct 7 |
Local and Adversarial Search |
AIMA Ch. 4.1, 5 |
PDF
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| Wed, Oct 9 |
Minimax and Alpha-Beta Search |
AIMA Ch. 5 |
PDF
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| Fri, Oct 11 |
Expectimax and Expectiminimax Search |
AIMA Ch. 5 |
PDF
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Project #1 due Sunday before midnight |
| Mon, Oct 14 |
Wumpus and Logical Agents |
AIMA Ch. 7 |
PDF
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Project #2 assigned |
| Wed, Oct 16 |
Wumpus Reasoning: Propositional Logic and Resolution |
AIMA Ch. 7 |
PDF
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| Fri, Oct 18 |
More on Inference in Propositional Logic |
AIMA Ch. 7 |
PDF
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| Mon, Oct 21 |
First-Order Logic |
AIMA Ch. 8 |
PDF
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| Wed, Oct 23 |
Inference using First-Order Logic |
AIMA Ch. 9 |
PDF
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| Fri, Oct 25 |
Midterm Review and Wrap-up of First-Order Logic |
AIMA Ch. 1-3, 4.1, 5, 7-9 |
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Project #2 due **Saturday Oct 26 before NOON** |
| Mon, Oct 28 |
Midterm Exam |
AIMA Ch. 1-3, 4.1, 5, 7-9 |
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| Wed, Oct 30 |
Markov Decision Processes (MDPs) (Part I) |
AIMA Ch. 13, 17 |
PDF
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| Fri, Nov 1 |
Markov Decision Processes (MDPs) (Part II) |
AIMA Ch. 17 |
PDF
Value iteration video |
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| Mon, Nov 4 |
Reinforcement Learning (RL) (Part I) |
AIMA Ch. 17 & 21 |
PDF
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Project #3 assigned |
| Wed, Nov 6 |
Reinforcement Learning (RL) (Part II) |
AIMA Ch. 17 & 21 |
PDF
Manual control Q-learning video
Epsilon-Greedy Q-learning video |
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| Fri, Nov 8 |
Feature-based Q-Learning and Uncertainty |
AIMA Ch. 13 |
PDF
Video: Q-learning, no features, 50 trials
Video: Q-learning, no features, 1000 trials
Video: Feature-based Q-learning, 50 trials
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| Mon, Nov 11 |
UW holiday |
AIMA Ch. 13 & 14 |
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| Wed, Nov 13 |
Probabilistic Inference |
AIMA Ch. 13 & 14 |
PDF |
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| Fri, Nov 15 |
Bayesian Networks |
AIMA Ch. 14 |
PDF |
Project #3 due Sunday before midnight |
| Mon, Nov 18 |
Inference in Bayesian Networks |
AIMA Ch. 15 |
PDF
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Project #4 assigned Tue, Nov 19 |
| Wed, Nov 20 |
Hidden Markov Models (HMMs) and Particle Filtering |
AIMA Ch. 15 |
PDF
Video: Filtering (tracking) using the Forward Algorithm
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| Fri, Nov 22 |
Particle Filtering and Machine Learning |
AIMA Chs. 15 and 18 |
PDF
Video: Particle filtering with 25 particles
Video: Particle filtering with 300 particles
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| Mon, Nov 25 |
Machine Learning: Decision Trees |
AIMA Ch. 18 |
PDF
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| Wed, Nov 27 |
Machine Learning: Support Vector Machines and Nearest Neighbors |
AIMA Ch. 18 |
PDF
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| Fri, Nov 29 |
Thanksgiving: UW holiday |
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| Mon, Dec 2 |
Machine Learning: Neural Networks |
AIMA Ch. 18 |
PDF
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| Wed, Dec 4 |
Machine Learning: Neural Networks and Ensemble Learning |
AIMA Ch. 18 |
PDF
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Project #4 due TODAY (Wed, Dec 4) before midnight |
| Fri, Dec 6 |
Course Summary and Survey of AI Applications |
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PDF
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TAKE HOME Final Exam will be available on Sunday Dec 8 by 10:30am
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CSE Home 
