Spring 2015 Syllabus

Week	Day(mm/dd)	Topic	Slides	Video	Assignment	Due(mm/dd)
1	2/6-2/12	Introduction to AI Overview Agents: Perception, Decisions, and Actuation	small large	Lec 1 720p 360p	Python Refresher	(ungraded)

2	2/13-2/19	Search and Planning Uninformed Search (Depth-First, Breadth-First, Uniform-Cost) Informed Search (A*, Greedy Search) Heuristics and Optimality	small large	Lec 2 720p 360p Lec 3 720p 360p	HW1: Search	2/22

3	2/20-2/26	Project 1: Search and Planning			P1: Search	3/1

4	2/27-3/5	Constraint Satisfaction Problems Backtracking Search Constraint Propagation (Forward Checking, Arc Consistency) Exploiting Graph Structure	small large	Lec 4 720p 360p Lec 5 720p 360p	HW2: CSPs	3/9

5	3/6-3/12	Game Trees and Decision Theory Game Trees and Tree-Structured Computation Minimax, Expectimax, Combinations Evaluation Functions and Approximations Alpha-Beta Pruning Decision Theory Preferences, Rationality, and Utilities Maximum Expected Utility	small large	Lec 6 720p 360p Lec 7 720p 360p Other Subtitle Step-By-Step	HW3: Games	3/15

6	3/13-3/19	Project 2: Game Trees and Decision Theory			P2: Multi-Agent Games	3/22

7	3/20-3/26	Markov Decision Processes (MDPs) Policies, Rewards, and Values Value Iteration Policy Iteration	small large	Lec 8 720p 360p Lec 9 720p 360p Subtitle	HW4: MDPs	3/29

8	3/27-4/2	Reinforcement Learning (RL) TD/Q Learning Exploration Approximation	small large	Lec 10 720p 360p Lec 11 720p 360p Subtitle	HW5: RL	4/5

9	4/3-4/9	Project 3: Reinforcement Learning (RL)			P3: RL	4/12

10	4/10-4/16	Conclusion and Wrap-Up			Practice Finals I II III	(ungraded)

11	4/17-4/23	No Lecture, Final Exam Week			Final	4/26