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January
Monday	Tuesday	Wednesday	Thursday	Friday
02	03	04 14:30-15:20 Lecture EEB 125 Introduction, Agents. RN: Chapter 3, Sections 3.1-3.4. Slides	05	06 14:30-15:20 Lecture EEB 125 Problem Spaces and Blind Search. RN: Chapter 3, Sections 3.5-3.6. Slides
09 14:30-15:20 Lecture EEB 125 Best-first and Uniform-Cost Search RN: Chapter 3, Sections 3.5-3.7 Slides	10	11 14:30-15:20 Lecture EEB 125 A* Search and Heuristics RN: Chapter 4, Sections 4.1-4.2. (continuation of the previous slide set) 23:59 Project 0 (Python tutorial) due	12	13 14:30-15:20 Lecture EEB 125 More on heuristics and search Slides
16 Martin Luther King Day	17	18 14:30-15:20 Lecture EEB 125 Constraint Satisfaction Problems, Part 1 RN: Chapter 3, Section 3.7, plus review of pp.104-105 in Chapter 4. Slides	19	20 14:30-15:20 Lecture EEB 125 Constraint Satisfaction Problems, Part 2 Slides
23 14:30-15:20 Lecture EEB 125 Adversarial Search, Minimax, Alpha-beta Search RN: Chapter 5, Sections 5.1-5.3 Slides 23:59 Project 1 (Search in PacMan) due	24	25 14:30-15:20 Lecture EEB 125 Uncertainty, Expectimax Search RN: Chapter 5, Sections 5.4, 5.5, 5.7, 5.9 Slides	26	27 14:30-15:20 Lecture EEB 125 Markov Decision Processes (MDPs) RN: Chapter 17, Sections 17.1, 17.2 Slides
30 14:30-15:20 Lecture EEB 125 MDPs: Value Iteration RN: Chapter 17, Sections 17.1, 17.2	31	01 14:30-15:20 Lecture EEB 125 MDPs: Policy Iteration RN: Chapter 17, Sections 17.2, 17.3 Slides	02	03 14:30-15:20 Lecture EEB 125 Reinforcement Learning RN: Chapter 21, Sections 21.1, 21.2, also Sutton and Barto: Draft 2nd ed. pages 1-144. Slides 23:59 Project 2 (Multiagent PacMan) due

February
Monday	Tuesday	Wednesday	Thursday	Friday
06 14:30-15:20 Lecture EEB 125 (UW classes cancelled due to snow) RN: Chapter 21, Sections 21.3, 21.4	07	08 14:30-15:20 Lecture EEB 125 RL Continued RN: Chapter 21, Sections 21.5	09	10 14:30-15:20 Lecture EEB 125 RL Continued (Q-Learning) Slides
13 14:30-15:20 Lecture EEB 125 RL Continued (Approximate Q-Learning) Slides (cont.)	14	15 14:30-15:20 Lecture EEB 125 Probabilities RN: Chapter 13, Sections 13.1-13.3 Slides 23:59 Project 3 (Reinforcement Learning) due	16	17 14:30-15:20 Midterm
20 Presidents Day	21	22 14:30-15:20 Lecture EEB 125 Probabilities (cont); Markov Models; RN: Chapter 13, Sections 13.3-13.5, 13.7 Slides	23	24 14:30-15:20 Lecture EEB 125 Hidden Markov Models RN: Chapter 15, Section 15.3 Slides
27 14:30-15:20 Lecture EEB 125 Particle Filters for HMMs RN: Chapter 15, Section 15.5	28	01 14:30-15:20 Lecture EEB 125 Bayes Nets RN: Chapter 14, Sections 14.1, 14.2 Slides	02	03 14:30-15:20 Lecture EEB 125 Perceptrons and Feedforward Neural Nets RN: Chapter 18, Section 18.7 Slides 23:59 Project 4 (Ghostbusters) due

March
Monday	Tuesday	Wednesday	Thursday	Friday
06 14:30-15:20 Lecture EEB 125 Naive Bayes Classification RN: p.499, pp.808-809. Slides 23:59 Optional Competition (PacMan Capture The Flag) due	07	08 14:30-15:20 Lecture EEB 125 Continuation of Naive Bayes Classification and Perceptrons. Slides	09	10 14:30-15:20 Lecture EEB 125 Competition final round. Wrap-up. Course evaluations. Slides 23:59 Project 5 (Pattern Classification) due
13	14 14:30-16:20 Final exam	15	16	17