CMSC 671: Introduction to Artificial Intelligence
Fall 2010

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Schedule

This is a tentative syllabus. Topics, reading assignments, homeworks, and exam dates are subject to change.

Reading chapters refer to course book (Russell and Norvig, Third Edition). We will follow the textbook fairly closely, with some additional background material on other topics of interest.

I will keep updating this page, specially with additional reading assignments.

Date

Topic

Reading Materials

Homework

Introduction

Aug. 31

Course overview; what is AI?

Ch. 1; McCarthy paper

Pretest out

Sep. 2

Agents

Ch. 2

 

Problem Solving and Search

Sep. 7

Lisp; Problem solving as search; Uninformed search

Ch. 3.1 - 3.4; Beating the Averages by Paul Graham

Pretest due

HW1 out

Sep. 9

Informed search; Heuristic functions

Ch. 3.5 - 3.7

 

Sep. 14

Local search algorithms

Ch. 4.1, 4.5, 4.6

 

Sep. 16

Constraint satisfaction

Ch. 6; Vipin Kumar, "Algorithms for Constraint Satisfaction Problems: A Survey"; Roman Bartak, "Constraint Programming: In Pursuit of the Holy Grail"

 

Sep. 18

no class

 

HW1 due

Sep. 21

Games (Adversarial Search)

Ch. 5

HW2 out

Sep. 23

Review; Advanced Search Methods; DCSP

Asynchronous Backtracking (Yokoo et al., 1992)
Asynchronous Weak-Commitment Search (Yokoo, 1995)

 

Logical Reasoning

Sep. 28

Knowledge-based agents; propositional logic

Ch. 7

 

Sep. 30

First-order logic

Ch. 8

 

Oct. 5

Lisp and Hommework 2
Search algorithms in Lisp

 

Oct. 7

Inference in First-order logic

Ch. 9

 

Oct.12

Knowledge representation

Ch. 12

 

Planning

Oct. 14

Classical Planning

Ch. 10.1-10.2

HW3 out

Oct. 16

no class

 

HW2 due

Oct. 19

Review and Graph-based planning

Ch. 10.3

Oct. 21

MIDTERM

Slides and chapters up until the Oct. 12th class
Some notes on the test; Links to old tests

Oct. 26

Scheduling and hierarchical planning

Ch. 11.1-11.2, 11.4

HW3 due

Uncertainty and Decision Making

Oct. 28

Semantic Web and OWL
Quantifying Uncertainty; Bayes’ Rule; Probabilistic Reasoning

Ch.13; Creating and Exploiting a Web of Semantic Data, Tim Finin

HW4 out

Nov. 2

Bayesian Networks

Ch. 14.1-14.5

Nov. 4

Probabilistic reasoning over time

Ch. 15.1-15.2

 

Nov. 9

Decision theory;
Machine Learning: Decision Trees

Ch. 16

HW4 due

Nov. 11

NO CLASS

Nov. 13

no class

FP Deliverable 1 due

Machine Learning

Nov. 16

Machine Learning (1)

Ch. 18.1-18.4; 18.8; 18.9

Nov. 18

Machine Learning (2)

Ch.21

Nov. 19

no class

FP Deliverable 2 due; HW5 out

Nov. 23

Machine Learning (3) (previous classes slides)

Ch.20 

Nov. 25

No Class: Thanks Giving Break

 

 

Nov. 30

Reinforcement learning

HW5 due

Multi-Agent Systems

Dec. 2

Multi-agent systems

 

 

Final Presentations and Exam

Dec. 7

Review and exercises

Exam guide

 

Dec. 14 2:00pm to 4:00 pm

Student Presentations (session will run from 2:00pm to 4:00 pm)

Student presentations guidelines

 

Dec. 16, 2:15 pm

FINAL EXAM

Slides and chapters starting from Oct. 14th class
Exam guide; New links to old tests are at the bottom of the Links page

Dec. 18, midnight

FP REPORT DUE

FP Report guidelines