Summer 2014 Syllabus
This syllabus is subject to change. In particular, the unreleased project out and due dates will likely change somewhat. Office hours may also move in certain weeks, see announcements for changes.
| Day | Topic | Optional Reading | Slides | Assignment | Due |
| Tue 6/24 | Introduction to AI | Ch. 1 | 1PP · 2PP 4PP · 6PP |
P0: Tutorial | Wed 6/25 |
| Wed 6/25 | Uninformed Search | Ch. 3.1-4 (2e: Ch. 3) | 1PP · 2PP 4PP · 6PP |
HW1 | Fri 6/27 |
| Thu 6/26 | A* Search and Heuristics | Ch. 3.5-6 (2e: Ch. 4.1-2) | 1PP · 2PP 4PP · 6PP |
P1: Search (section / solutions) |
Mon 6/30 |
| Mon 6/30 | Constraint Satisfaction Problems | Ch. 6.1 (2e: Ch. 5.1) Backtracking Demo |
1PP · 2PP 4PP · 6PP |
HW2 | Wed 7/2 |
| Tue 7/1 | CSPs II | Ch. 6.2-5 (2e: Ch. 5.2-4) | 1PP · 2PP 4PP · 6PP |
(section / solutions) (section / solutions) |
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| Wed 7/2 | Game Trees: Minimax | Ch. 5.2-5 (2e: Ch. 6.2-5) | 1PP · 2PP 4PP · 6PP |
HW3 (optional) | |
| Thu 7/3 | Game Trees: Expectimax; Utilities | Ch. 5.2-5 (2e: Ch. 6.2-5), 16.1-16.3 | 1PP · 2PP 4PP · 6PP |
P2: Multi-Agent Pacman (section / solutions) |
Mon 7/7 |
| Mon 7/7 | Markov Decision Processes | Ch. 17.1-3 | 1PP · 2PP 4PP · 6PP |
HW4 | Wed 7/9 |
| Tue 7/8 | Markov Decision Processes II | Ch. 17.1-3, Sutton and Barto Ch. 3-4 | 1PP · 2PP 4PP · 6PP |
(section / solutions) | |
| Wed 7/9 | Reinforcement Learning | Ch. 21, S&B Ch. 6.1,2,5 | 1PP · 2PP 4PP · 6PP |
P3: Reinforcement Learning HW5 |
Mon 7/14 Fri 7/11 |
| Thu 7/10 | Reinforcement Learning II | Ch. 21 | 1PP · 2PP 4PP · 6PP |
Practice Midterm (section / solutions) |
Tue 7/15 |
| Mon 7/14 | Review | |
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| Tue 7/15 | No Lecture | |
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| Wed 7/16 | Midterm, (3-6 PM, 245 Li Ka Shing) | |
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| Thu 7/17 | Probability | Ch. 13.1-5 (2e: Ch. 13.1-6) | 1PP · 2PP 4PP · 6PP |
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| Mon 7/21 | Bayes' Nets: Representation | Ch. 14.1-2,4 | 1PP · 2PP 4PP · 6PP |
HW6 | 7/24 |
| Tue 7/22 | Bayes' Nets: Independence | Ch. 14.1-2,4 | 1PP · 2PP 4PP · 6PP |
(section / solutions) | |
| Wed 7/23 | Bayes' Nets: Inference | Ch. 14.4, Jordan 2.1 | 1PP · 2PP 4PP · 6PP |
7/28 | |
| Thu 7/24 | Bayes' Nets: Sampling | Ch. 14.4-5 | 1PP · 2PP 4PP · 6PP |
HW7 (section / solutions) |
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| Mon 7/28 | Decision Diagrams / VPI | Ch. 16.5-6 | 1PP · 2PP 4PP · 6PP |
HW8 | 7/31 |
| Tue 7/29 | Markov Models | Ch. 15.2,5 | 1PP · 2PP 4PP · 6PP |
(section / solutions) | |
| Wed 7/30 | Hidden Markov Models | Ch. 15.2,5 | 1PP · 2PP 4PP · 6PP |
P4: Ghostbusters | 8/5 |
| Thu 7/31 | Applications of HMMs | Ch. 15.2,6 | 1PP · 2PP 4PP · 6PP |
(section / solutions) | |
| Mon 8/4 | ML: Naive Bayes | Ch. 20.1-20.2.2 | 1PP · 2PP 4PP · 6PP |
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| Tue 8/5 | ML: Perceptrons | Ch. 18.6.3 | 1PP · 2PP 4PP · 6PP |
Final Contest (section / solutions) |
8/11 |
| Wed 8/6 | ML: Kernels and Clustering | Ch. 18.8 | 1PP · 2PP 4PP · 6PP |
HW9 | 8/11 |
| Thu 8/7 | Advanced Applications: (Robotics and Computer Vision) | 1PP · 2PP 4PP · 6PP |
Practice Final (section / solutions) |
8/12 | |
| Mon 8/11 | Advanced Applications: NLP, Games and Cars | 1PP · 2PP 4PP · 6PP |
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| Tue 8/12 | Review | 1PP · 2PP 4PP · 6PP |
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| Wed 8/13 | Advanced Topics and Final Contest | 1PP · 2PP 4PP · 6PP |
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| Thu 8/14 | Final Exam, (3-6 PM, 245 Li Ka Shing) | |
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