CS 490: Artificial Intelligence (Fall 2012)

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CS 490: Artificial Intelligence (Fall 2012)


Catalog Description and Course Credit Hours



CS490. ARTIFICIAL INTELLIGENCE (4)


Artificial Intelligence.
An introduction to

Artificial Intelligence with LISP
and PROLOG covering

fundamental constructs and algorithms, various knowledge

representations and advanced topics. Prerequisite:

CS 300 with a minimum grade of ‘C’
and two upper

l
evel CS courses.

(4)

(Three hours course and two hours lab a week.)


INSTRUCTOR: Dr.
Xuesong Zhan
g

e
-
mail:

xzhang
@semo.edu

CLASS HOUR: 1:30
-
2:45PM
Monday

&

Wednesday


1:30
-
3:20PM Friday

CLASS LOCATION: Monday & Wednesday: DH024
,



Friday: DH026

OFFICE: DH021
C

Dempster Hall, Phone: 651
-
2788


OFFICE HOURS: Monday

&
Wednesday 3:00

-
4:30PM

and by appointment




***Office hours subject to change due to special circumstances.

Textbooks:
Artificial Intelligence Illuminated

by Ben Coppin, Jones and Bartlett


Publishers, 2004.



Student Learning Oblectives:

1. Students will be able to explain major algorithms and methods used in


artificial intelligence.

2. Students will be able to u
se artificial intelligence methods to represent


some real world knowledge.

3. Students will be able to write computer programs by using artificial


intelligence methods.

Tentative Schedule:
We will follow the chapter orders in the textbook with some add



on examples and some omissions.

Tentative Course Outline:


Start


Topics *





Reference


Week










in text


1

Week01

Part 1
. Course overview, a brief introduction and
history of Artificial Intelligence.

Chap 1,2

2

Week02

Part 1
. Knowledge Representation,

Chap 3

3

Week04

Part 2.

Search Methodologies


Chap 4, 5

4

Week04

Part 2
.
Search Methodologies and Part 3.
Propositional and Predicate Logic

Chap 6, 7

5

Feb 1
7

Test
-
1

on Friday, 09/21


6

Week05

Inference and Resolution for Problem Solving,
Rules and Expert Systems Part 4.

Introduction to
Machine Learning, Neural Networks.

Chap 8,
9, 10


2

7

Week06

Part 4.
Neural Networks, Probabilistic Reasoning
and Bayesian Networks.

Chap 11,
12

8

Week07

Part4.

Artificial Life and Genetic Algorithms.


Chap
13,14

9

Week08

Part4.

Artificial Life and Genetic Algorithms

March 12
-
22, Spring
break

Chapter
13, 14, 15

1
1

Week09

Mid
-
term on
Friday
,
10
/
19


1
2

Week10

Part5
. Introduction to Planning and Planning
Method.

Chap 16,
17

1
3

Week11

Part 6
.

Advanced Knowledge Representation.

Part 6
.
Fuzzy Reasoning.

Chap 18

1
4

Week12

Part 6
.
Intelligent Agents.


Test 3:
Friday
,
11
/
16

Chap 19

1
5

Week13

Part 6.
Understanding Language.

Chap 20

1
6

Week14

Part 6.

Machine Vision

Chap 21

17

Week15

Course Review and Summary

Ch 1
-

21

18

Week16

Final Exam

on
12:00 Wednesday,12/12



Grading:

Exams:
Three major exams (30%)


H
omework and lab (
4
5%), and quiz (5%)


Final exam: (
2
0%)

Grades: A: 90
-
100


B: 80
-
89


C: 70
-
79


D: 60
-
69


F: <60