This page is for the 2019 Spring version of this class. For general information concerning this course, refer to the general course page.

Date	Topic	Readings:	Lecture	Assignment/Lab
	What is AI?	Ch 1 (sect 1.1, 1.2.2, 1.2.3)	Lecture 1
	Intelligent Agents	Chapter 2 (all)	Lecture 2
	Uninformed Search	Chapter 3 (pages 64 - 91)	Lecture 3
	Informed Search	Chapter 3 (pages 92 - 109)	Lecture 4
	Hill climbers, simulated annealing, beam search	Chapter 4 (pg. 120 - 126)	Lecture 5	Assignment 1 (due Jan 31)
	Genetic Algorithms, Continuous Spaces	Chapter 4 (pg. 126 - 133)	Lecture 6
	Nondeterministic Actions Partial Observations	Chapter 4 (pg. 133 - 147)	Lecture 7
	Adversarial Search	Chapter 5 (pg. 161-170)	Lecture 8
	No Class
	Midterm Exam 1
	α / β pruning Stochastic Games Partially Observable Games	Chapter 5 (pg. 180-185)	Lecture 9	Assignment 2 (due Feb 21)
	Constraint Satisfaction Problems	Chapter 6 (6.1 - 6.2)	Lecture 10
	Constraint Satisfaction Problems	Chapter 6 (6.3 - 6.6)	Lecture 11
	Logical Agents/Propositional Logic	Chapter 7 (7.1 - 7.4)	Lecture 12
	Theorem Proving	Chapter 8 (pg. 285-313)	Lecture 13
	First Order Logic	Chapter 9 (pg. 322 - 345)	Lecture 14
	Spring Break
	Spring Break
	Inference in FOL/Review	Chp 9 (9.1, 9.2, 9.3, 9.4) (exclude 9.4.3)	Lecture 15
	Inference in FOL/Review	Chp 9 (9.5)	Lecture 16
	Midterm Exam 2		Lecture 16
	Reasoning w/Uncertainty	Chapter 13 (13.1 - 13.5)	Lecture 17
	Probabilistic Reasoning	Chapter 14 (14.1 - 14.2)	Lecture 18
	Probabilistic Reasoning	Chapter 14 (14.2)	Lecture 19
	Probablistic Reasoning	Chapter 14 (14.3 - 14.4)	Lecture 20	Assignment 3 (due Apr 21)
	Probablistic Reasoning	Chapter 14 (14.5)	Lecture 21
	Probablistic Reasoning over Time	Chapter 15 (15.1 - 15.3)	Lecture 22
	Probablstic Reasoning over Time	Chapter 15 (15.4 - 15.5)	Lecture 23
	Learning Probabilistic Models	Chapter 21 (pg. 830 - 853)	Lecture 24
	Reinforcement Learning
	Project Discussions
	Final Project Due
	Final Exam (Time: 1:00 pm to 3:00 pm)	Final Review