CMSC 421: Introduction to AI - Fall 2004


Lectures and Assignments

These abbreviations are used in the following assignments:


Course Summary and Reading Assignments
 Date Lecture Topics Assigned Readings
8/31 Introduction to AI
(Lecture Slides, PDF Format)
R&N:
    Ch. 1 (omit Sect. 1.2),
    Ch. 2 (omit Sect. 2.3),
    Ch. 26
9/2 Evaluating Symbolic
    Expressions
ACL: 1-24, 31-55, 195-199
9/7 Functional Programming I ACL: 114-116, 143-150, 287-294
9/9 Functional Programming II ACL: 133-138, 201-203, 208-211
9/14 Lisp Programming ACL: 81-92, 102-103, 119-125, 130-131
9/16 Applicative Operators
Lambda expressions
ACL: 25-27
9/21 Macros ACL: 160-173
9/23 AI Associative Databases   ----
9/28 State Space Representation
State Space Search I
R&N: 59-83
9/30 State Space Search II R&N: 94-101
10/5 Algorithm A*
Constraint Satisfaction
    Problems I
R&N: 105-106
R&N: 137-147
 
10/7 CSP II
(Lecture Slides, PDF Format)
Adversarial Search
 
 
R&N: 161-167
10/12 Project Discussion
 
 
Assignment 3 Review
Lisp Review
Constructor Code (plain text)
Chem. Spill Vocab. Source (plain text)
Statistics Vocab. Source (plain text)
 
 
10/14   -- MIDTERM EXAM --   ------
10/19 Review of Midterm Answers
Class Project Discussion
Alpha-Beta Search
 
 
R&N: 167-171, 180-185
10/21 Problem Reduction
Hill Climbing
(Lecture Slides, PDF format)
Intro. to Theorem Proving
 
R&N: 110-114, 150-151
 
R&N: 194-197, 200-207
10/26 Resolution in Propositional Logic R&N: 210-217, 245-256
10/28 Resolution in FOPC R&N: 272-278, 295-300, 304-306
11/2 Logic Programming
and Prolog
R&N: 287-290
LIB: Clocksin & Mellish, Prolog, 1984, 1-21
11/4 Knowledge Engineering
(Lecture Slides, PDF format)
Rule-Based Expert Systems
R&N: 260-266, 217-220, 280-283
LIB: Gonzalez & Dankel, Engineering Knowledge-Based Systems, 1993, 86-99
11/9 Certainty Factors etc.
(Lecture Slides, PDF format)
Association-Based Abduction (Lecture Slides, PDF format)
R&N: 320-324, 349-352
 
LIB: Peng & Reggia, Abductive Inference Methods, 1990, 1-9, 20-24.
11/11 Probabilistic Inference (Lecture Slides, PDF format)
R&N: 462-482
11/16 Bayesian Classifiers
Bayesian Networks I
(Lecture Slides: see 11/18)
 
R&N: 492-501, 504-506
 
11/18 Bayesian Networks II
(Lecture Slides, PDF format)
 
Planning: STRIPS
(Lecture Slides: see 11/23)
R&N: 511-516
LIB: Peng & Reggia, Abductive Inference Methods, 1990, 99-100, 113-115.
R&N: 375-387
 
11/23 PO and HTN Planning
(Lecture Slides, PDF format)
R&N: 387-393, 422-430
 
11/25 no class (Thanksgiving) ---
11/30 Natural Language Processing
(Lecture Slides, PDF format)
 
R&N: 790-800, 818-824
LIB: Woods, Transition Network Grammars ... , CACM, 13, 1970, 591-596 only
12/2 Machine Learning
(Lecture Slides, PDF format)
Tree Induction
(Lecture Slides, PDF format)
R&N: 649-653
 
R&N: 653-664
 
12/7 Neural Networks
(Lecture Slides, PDF format)
R&N: 736-748
12/9 Error Backpropagation
Evolutionary Computation (Lecture Slides, PDF format)
 
R&N: 116-119
 
12/13 8 AM: -- FINAL EXAM -- ---


Back to CMSC 421 Home Page