BBE 4102 Intelligent Systemsx

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Oct 24, 2013 (3 years and 5 months ago)

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BBE 4102 Intelligent Systems

Course

description

Theory

and

i
m
ple
m
entation

of

a

variety

of

techniques

used

to

si
m
u
late

intelligent

behavior.

Expert
s
y
ste
m
s,

fuzzy

logic,

neural

networks,

evolutionary

co
m
putation,

and

two
-
pla
y
er

ga
m
e
-
tree

search

will
be

covered

in

depth.

Knowledge

representation,

pattern

recognit
i
on,

h
y
brid

approaches,

and

handling
uncertainty

will

also

be

discussed


Course

Objectives

By

covering

the

course

in

Intelligent

S
y
ste
m
s,

the

student

will

be

able

to:

1
.

Appreciate

the

concepts

of

Artificial

Intelligence

and

the

diversity

of

approaches

and

definitions
with

which

it

is

associated.

2
.

Develop

an

understanding

of

heuristic

m
ethods.

3
.

Learn

the

underl
y
ing

theory

and

practice

of

e
volutionary

co
m
putation,

including

genetic

algorith
m
s

and

genetic

progra
mm
ing.

4
.

Appreciate

knowledge

engineering,

develop

expert

s
y
ste
m
s,

and

understand

fuzzy

expert
s
y
ste
m
s.

5
.

Develop

an

understanding

of

and

i
m
p
l
e
m
ent

artificial

neural

networks.

6
.

I
m
ple
m
ent

a

two
-
pla
y
er

strategy

ga
m
e

with

opti
m
ized

adversarial

search.

7
.

I
m
ple
m
ent,

observe

and

evaluate

alternative

approaches

to

intelligent

s
y
ste
m
s


Course

Content

Optimi
z
a
tion

Methods




Gradient

m
ethods




Linear

Progra
mm
ing




Constrained

Proble
m
s

and

Lagrange

Multiplier

Method




Search

Method




Ordinal

Opti
m
ization




Genetic

Algorith
m
s




Applications

Fundamentals

of

Neural

Networks




Basic

concepts




Back
-
propagation

algorithm




Applications

Advanced

Neural

Networks




Co
m
p
etitive

learning




Data

clustering

networks




Application

in

hierarchical

m
odeling

for

co
m
p
lex

s
y
ste
m
s

Knowledge

Representation

Methods




Linguistic

knowledge

representation




Mathe
m
atical

foundation:

Random

Sets




Applications

Information

Fusion

Techniques




Fusion

of

linguistic

and

stochastic

infor
m
ation




Application

in

intelligent

seg
m
entation




Application

in

sensor

fusion


Reference

Materials

1
.

Michael

Negnevitsk
y
,

2005.

Artificial

Intelligence:

A

Guide

to

Intelligent

S
y
ste
m
s.

Addison
-

Wesle
y
-

ISBN

0321204662

72



2
.

George

F.

Luger,

Peder

Johnson,

Jean

E.

New
m
an,

Carl

Stern,

Ronald

Yeo

-

C
ognitive

Science:
The

Science

of

Intelligent

Systems.

Acade
m
ic

Press

(1994)

-

ISBN

0124595707

3
.

Jatinder

N.

D.

Gupta,

Guisseppi

A.

Forgionne,

Manuel

Mora.

Intelligent

Decision
-
making

Support

Systems:

Foundations,

Applications

and

Challenges.

Springer

(2006)
-
ISBN

1846282284


Require
m
ents


Hours

per

Se
m
ester

W
eighted

T
o
tal Mark

W
eighted

Exam

Mark

W
eighted

Continuous

Assess
m
ent Mark

Cre
d
it

U
n
its

LH

PH

TH

CH

W
TM

W
EM

W
CM

CU

45

30

00

60

100

60

40

4