Day | Topic | Reading | Slides | Out | Due | |
Tu 1/17 | Introduction to AI | Ch. 1 | 2PP 6PP | |||
Th 1/19 | Agents and Search | Ch. 3.1-4 (2e: 3) | 2PP 6PP | P0: Python Tutorial | 1/27 | |
Tu 1/24 | A* Search and Heuristics | Ch. 3.5-6 (2e: 4.1-2) | see previous lecture | P1: Search | 2/3 | |
Th 1/26 | Constraint Satisfaction Problems | Ch. 6.1 (2e: 5.1) | 2PP 6PP | |||
Tu 1/31 | CSPs II | Ch. 6.2-5 (2e: 5.2-4) | see previous lecture | |||
Th 2/2 | Game Trees: Minimax, Alpha-Beta | Ch. 5.2-5 (2e: 6.2-5) | 2PP 6PP | |||
Tu 2/7 | Game Trees: Expectimax; Utility Theory | Ch. 5.2-5 (2e: 6.2-5) | 2PP 6PP | P2: Multi-Agent Pacman | 2/17 | |
Th 2/9 | Markov Decision Processes | Sutton and Barto Ch. 3-4 | 2PP 6PP | |||
Tu 2/14 | MDPs II | Ch. 17.1-3 (2e: 17.1-3), Sutton and Barto Ch. 6.1,2,5 | see previous lecture | |||
Th 2/16 | Reinforcement Learning | 2PP 6PP | ||||
Tu 2/21 | Midterm I Review Lecture | 2PP 6PP practice midterm1 | ||||
Th 2/23 | Midterm I | LOCATION: 155 Dwinelle | ||||
Tu 2/28 | Reinforcement Learning II | see previous lecture on RL | P3: Reinforcement Learning | 3/12 | ||
Th 3/1 | Probability | Ch. 13.1-5 (2e: 13.1-6) | 2PP 6PP | |||
Tu 3/6 | Bayes' Nets: Representation | Ch. 14.1-2,4 (2e: 14.1-2,4) | 2PP 6PP | |||
Th 3/8 | Bayes' Nets: Independence | Ch. 14.3 (2e: 14.3), Jordan 2.1 | see previous lecture | |||
Tu 3/13 | Bayes' Nets: Inference | Ch. 14.4-5 (2e: 14.4-5) | 2PP 6PP | |||
Th 3/15 | Bayes' Nets: Sampling | Ch. 14.4-5 (2e: 14.4-5) | see previous lecture | |||
Tu 3/20 | Midterm II Review Lecture | 2PP 6PP | ||||
Th 3/22 | Midterm II | LOCATION: 2050 Valley LSB | ||||
Tu 3/27 |
Spring Break |
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Th 3/29 |
Spring Break |
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Tu 4/3 | HMMs, DBNs, Particle Filtering, Viterbi | Ch. 15.2,5-6 (2e: 15.2,5-6) | 2PP 6PP | P4: Ghostbusters | 4/17 | |
Th 4/5 | Speech | Ch. 15.1-3,6 (2e: 15.1-3,6) | 2PP 6PP | Contest: Pacman Capture The Flag | 4/25 [Wednesday!] | |
Tu 4/10 | Decision Diagrams, VPI | Ch. 16.5-6 | 2PP 6PP | |||
Th 4/12 | ML: Naive Bayes | Ch. 20.1, 20.2.1, 20.2.2 | 2PP 6PP | |||
Tu 4/17 | ML: Perceptron and Optimization | 2PP 6PP | P5: Classification | 4/30 | ||
Th 4/19 | ML: Perceptron and Optimization (ctd) | see previous lecture | ||||
Tu 4/24 | Applications: Robotics [not study material for final] | 2PP 6PP | ||||
Th 4/26 | Applications: Computer Vision, Language; Final Contest and Conclusion [not study material for final] | 2PP 6PP 2PP 6PP | ||||
Tu 5/1 | Final Review Session 1: Search, CSPs, Game Trees, Utility, MDPs, RL | 2PP 6PP 2PP 6PP | ||||
Th 5/3 | Final Review Session 2: Probability, Bayes' Nets, HMMs, DBNs, Particle Filtering, Viterbi, Decision Diagrams, VPI, ML | 2PP 6PP 2PP 6PP | ||||
F 5/11 | Final Exam 11:30-2:30pm, 1 Pimentel |