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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 operation of intelligent agents, intelligent search (solutiondiscovering) algorithms and constraint satisfaction problems, First-Order
Logic and its inference, Knowledge Representation, Planning, Uncertainty
and Bayesian Networks, and Machine Learning. For all 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/tariqmahmood/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 (2nd Edition),
by Stuart Russell and Peter Norvig
Reference Textbooks: Artificial Intelligence: A Guide To Intelligent
Systems (2nd 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
1
2
3
Introduction to AI – History and Background
Rational (Intelligent) Agents and their Operation
Basic Solution Search Techniques – Depth-First,
Breadth-First, A*, Simulated Annealing, Hill Climbing
etc.
Advanced Solution Search Techniques – Minimax,
alpha-beta pruning etc.
Constraint Satisfaction Problems
First Order Logic and Its Inference – Forward
Chaining, Backward Chaining, Resolution etc.
Knowledge Representation and Reasoning
Planning (State-Space Search) and Acting in the Real
World
[Uncertainty] Uncertain Behavior, Probabilistic
Reasoning, Bayesian Networks, and Current Research
Trends
[Decision Theory] Utility Theory, Game Theory,
Decision Networks, Simple and Complex Decisions etc.,
and Current Research Trends
[Machine Learning] Supervised Learning:
Techniques, Applications (All Types of Recognitions and
Classifications), and Current Research Trends
[Machine Learning] Reinforcement Learning:
Techniques (various algorithms such as Value Iteration,
Policy Iteration, Q-learning), Applications, and Current
Research Trends
[Machine Learning] Unsupervised Learning:
Techniques (various algorithms such as SOM),
Applications, and Current Research Trends
Natural Language Processing: Techniques,
Application, and Current Research Trends
4
5
6
7
8
9
10
11
12
13
14
No. Of
Lectures
1
2
1
2
1
2
2
3
4
4
2
2
2
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 assignments 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 classes. 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 class 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.