CMSC 421
Introduction to Artificial Intelligence
Fall 2005

Approximate Schedule*


This schedule shows for each class session: the topics that will be covered, the required and optional readings and any assignments that are due that day. Readings should be done before the class meeting. All homework and programming assignments are due at the beginning of class. THIS SCHEDULE WILL CHANGE, PLEASE CHECK IT REGULARLY!


Session Date Topic Notes Required
Reading
Assignment
slides**
1
Sep 1
Introduction and Course Overview  
ch. 1
2
Sep 6
Intelligent Agents & Problem Solving  
ch. 2
 
3
Sep 8
Search  
ch. 3
 hw1 handed out
4
Sep 13
Heuristic Search

 

ch. 4
 
5
Sep 15
Constraint Satisfaction Problems (CSPs)  
ch. 5

 hw1 due

hw1 solutions

6
Sep 20
CSPs  
 
 pa1 handed out
 
7
Sep 22
Game Playing  
 ch. 6
 
slides 
8
Sep 27
Game Playing  
  pa1 Part A due
 
9
Sep 29
KR & Logical Agents  
ch. 7
  pa1 Part B due Fri 9/30 6PM
slides 
11
Oct 4
Resolution & Theorem Proving  
 hw2 handed out
 
10
Oct 6
First Order Logic (FOL)  
ch. 8
 
12
Oct 11
FOL & Theorem Proving  
ch. 9  
 

 

13
Oct 13
Review      
14
Oct 18
MIDTERM
15
Oct 20
Planning  
ch. 11
 hw3 handed out
16
Oct 25
Planning  
 
 
 
17
Oct 27
Planning  
ch 12
 
18
Nov 1
Uncertainty  
ch. 13

 hw3 due

hw3 solutions

19
Nov 3
Proabalistic Reasoning  
ch 14
 hw4 handed out
20
Nov 8
Probabilistic Reasoning  
 
21
Nov 10
Probabilistic Reasoning  
ch 15
 
22
Nov 15
Decision Making Under Uncertainty  
ch 16

 hw4 due

hw4 solutions

 
23
Nov 17
Decision Making Under Uncertainty  
ch 17
 
24
Nov 22
Learning  
ch 18
 
25
Nov 29
Reinforcement Learning  
ch 21
 
26
Dec 1
Reinforcement Learning  
ch 21
 pa2 instructions
 
27
Dec 6
Learning  
ch 19
 hw5 handed out (OPTIONAL)
 
28
Dec 8
Learning  
ch 20
 
29
Dec 13
Wrap-up  

 hw5 due

hw5 solutions

 
FINAL EXAM Wednesday, Dec 21 10:30am-12:30pm

 

Key:
RN = Russell & Norvig, Artificial Intelligence: A Modern Approach
H = homework assignment
P = project

* This schedule is subject to change. Please check it periodically.

** The course slides are based in part on the course notes of Jean-Claude Latombe at Stanford, Marie desJardins at UMBC, Daphne Koller at Stanford and others.

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