Course Schedule

In the readings, RN refers to Russell and Norvig; SB refers to Sutton and Barto.

Meeting	Topics	Readings
9 Jan	What is Artificial Intelligence?	opt: RN 1.1,2
Search
11 Jan	Search I Depth and breadth first search	3.1,3.3,3.4 opt: RN 3.2
16 Jan	Search II A* search and heuristics	3.5-3.6 opt: RN 4.1-4.2
18 Jan	Predicate Logic & Knowledge Representation	RN 8, 9, 11
23 Jan	STRIPS & Classical Planning	RN 10
25 Jan	Lab for Project 1	No Redaing
30 Jan	Constraint Satisfaction Problems Search, constraints and filtering	RN 6-6.3
1 Feb	Game Playing I Minimax search	RN 5-5.3
6 Feb	Game Playing II Expectimax search	RN 5.4-5.5
8 Feb	Probability Everything you need to know!	RN 13-13.5 opt: RN 13.6
13 Feb	Utility / Exam 1 Review Consistency and risk	16-16.3 opt: RN 16.4
15 Feb	Exam 1
Reinforcement Learning
20 Feb	Markov Decision Processes I Value iteration	RN 17.1-2 SB 3, 4.4
22 Feb	Markov Decision Processes II Policy iteration	RN 17.3 SB 4.1-3
27 Feb	Project 3 Lab	No reading
1 Mar	Reinforcement Learning I TD-learning & Q-Learning	RN 21.1-2 SB 6.1-4
6 Mar	Reinforcement Learning II Function Approximation, Least Squares	RN 21.3 SB 6.5
8 Mar	Reinforcement Learning III Policy Representation and Policy Search	RN 21.4-5 SB 8.1,8.2
13 Mar	Reinforcement Learning IV Monte Carlo Tree Search & Alpha Go
15 Mar	Exam II
20/22 Mar	Spring break
Reasoning Under Uncertainty
27 Mar	Bayes' Nets I Representation	RN 14-14.4
29 Mar	Bayes' Nets II Independence, inference	RN 14.4
3 April	Bayes' Nets III Sampling	RN 14.5
5 April	Lab for Project 4
10 April	Hidden Markov Models I Filtering	RN 15.2
12 April	Hidden Markov Models II Particle filtering, Dynamic Bayes Nets, Viterbi algorithm	RN 15.5
17 April	Partially-Observable Markov Decision Processes I Representation, value iteration	RN 17.4 Dummies Links to an external site., Sec 3-6
19 April	POMDP II Approximate solutions
24 April	Ethics & Philosophy Chinese Room, Sci-Fi, Hawking, Musk, etc Final Exam Review & Wrap Up
2 May	FINAL EXAM 10:30 am - 12:30 pm