Course Outline - WordPress – www.wordpress.com

stemswedishΤεχνίτη Νοημοσύνη και Ρομποτική

15 Οκτ 2013 (πριν από 3 χρόνια και 9 μήνες)

152 εμφανίσεις


ARTIFICIAL INTELLIGENCE



CS 401

COURSE
INFORMATION

FALL

2010



Undergraduate Level

Course Description:

This course provides a generic introduction and explanation of the most
prominent branches of the science of Artificial Intelligence (AI).

One of the
aims of this course is to introduce the undergrad students to the concept of
devising and implementing research
-
based projects, i.e., those projects
which have the potential to be presented as research work. Topics covered
will include the oper
ation of intelligent agents, intelligent search (solution
-
discovering) algorithms and constraint satisfaction problems, First
-
Order
Logic and its inference, Knowledge Representation, Planning, Uncertainty
and Bayesian Networks, and Machine Learning. For al
l these topics, students
will be introduced to the current implementation techniques and research
trends, in order to motivate them to develop these trends further.

Administrative Info:

Instructor
:
Dr. Tariq Mahmood

|
Office Hours: TBA


Course Website:
http://sites.google.com/a/nu.edu.pk/tariq
-
mahmood/teaching
-
1/artificial
-
intelligence
---
fall
-
2010
-
1

Sections

and Lectures
: 2
Sections
(A and B)

with
6 lectures/week

Primary
Textbook
:
Artificial Intelligence: A Modern Approach

(2
nd

Edition)
,
by Stuart Russel
l and Peter Norvig

Reference Textbook
s
:
Artificial Intelligence: A Guide To Intelligent
Systems

(2
nd

Edition), by Michael Negnevitsky
, and
Agent Technology For
Communication Infrastructures
, by Alex L. G. Hayzelden and Rachel A.
Bourne
.

Course Outline

In
all, there are a total of 14 topics divided over 30 lectures (the number of
lectures could change depending on how the semester rolls out):

Topic

Description

No. Of
Lectures

1

Introduction to AI



䡩獴o特⁡rd⁂慣歧牯und

1

2

Rational (
Intelligent
)

Agents

and their Operation

2

3

Basic
Solution Search
Techniques



䑥灴h
-
Fi牳r,
B牥慤th
-
Fi牳r,⁁*, Simul慴ed⁁nne慬ing,⁈ ll⁃ imbing
et挮

1

4

Advanced
Solution
Search Techniques



Minim慸,
慬pha
-
bet愠a牵ning et挮

2

5

Constraint Satisfaction Problems

1

6

First Order Logic and
Its
Inference



Fo牷慲搠
䍨慩ning,⁂慣歷慲 ⁃ 慩ning,⁒e獯汵tion⁥瑣.

2

7

Knowledge Representation and Reasoning

2

8

Planning

(State
-
Space Search)

and Acting in the Real
World

3

9

[Uncertainty]

Uncertain Behavior
, Probabilistic
Reas
oning,
Bayesian Networks
, and Current Research
Trends

4

10

[
Decision Theory
]

Utility Theory, Game Theory,
Decision Networks, Si
mple and Complex Decisions etc.,

and Current Research Trends

4

11

[Machine Learning]

Supervised Learning
:
Techniques
,
Applications (All Types of Recognitions and
Classifications), and Current Research Trends

2

12

[
Machine Learning
] Reinforcement Learning
:
Techniques

(various algorithms such as Value Iteration,
Policy Iteration, Q
-
learning)
,

Applications, and Current
Rese
arch Trends

2

13

[
Machine Learning
]

Unsupervised Learning
:
Techniques

(various algorithms such as SOM)
,

Applications, and Current Research Trends

2

14

Natural Language Processing
:

Techniques,
Application, and Current Research Trends

2


Grade
Distribution (/100%)

Mid
-
Term 1


10%, Mid
-
Term 2


10%, Final Exam


50%, Project


15%,
Assignments


10%, Quizzes


5%

Assignments
and Project

The students would be required to divide themselves into groups. Both the
assignments and the project are to
be submitted collectively by the whole
group. There would be three assignments, pertaining to the current contents
that being taught in the course, with weightages of 3%, 3% and 4%
respectively.

Cheating Policy

Simply put, any two or more matching assignme
nts will be marked directly
with a 0. No compromise or consultation would be permitted in this regard.

Attendance Policy

This is very strict. Absolutely no compromise would be made for those
students who are not motivated or serious enough to attend classe
s. My own
policy is that if you find the course uninteresting despite the efforts of the
teachers, then you should drop the course, rather than hanging on and
bunking classes.

Class Discipline Policy

Any student who is disrupting the environment of the cla
ss will simply be
asked to leave. If this student persists
with disruptive
demeanor, then
he/she will
be permanently disallowed from attending any further classes.
No compromise or complaints would be entertained in this regard.