Course syllabus IA

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Course syllabus
Academic Year (2023-2024)
Réf : GES-IMP-34
Indice : 01
Date :11/07/2023
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Course Syllabus
IA: Artificial intelligence
Academic Year(2023-2024)-Second Semester
Instructor :
Name : Ben Fradj HAJER
Contact inf : [email protected]
Phone : [phone]
Office hours :
Course Information :
Name : Artificial intelligence
Course ID : code U.E.2.7.3
Catolog number :
Cr hours : 45 (30 Theory, 15 Lab)
Contact hours : Theory 3 hours and Lab 3 hours
Course Prerequisites :
Algorithms and data structures, programming, probability and statistics.
Classroom Location and Time :
Class No.
Lecture
Lab
30 contact hours
15 contact lab
Text Books :
1. Murphy, K. P. Machine Learning: A Probabilistic Perspective. (2020).
2. Sutton, R., Barto, A. Reinforcement Learning: An Introduction. (2018).

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Course syllabus
Academic Year (2023-2024)
Réf : GES-IMP-34
Indice : 01
Date :11/07/2023
Page 2/1
References :
1. Russell, S., Norvig, P. Intelligence artificielle : Foundations of Artificial Intelligence. (2016).
2. Goodfellow, I., Bengio, Y., Courville, A. Deep Learning. (2020).
Courses description :
Artificial intelligence (AI) is a research field that studies how to realize the intelligent human behaviors
on a computer. The ultimate goal of AI is to make a computer that can learn, plan, and solve problems
autonomously. Although AI has been studied for more than half a century, we still cannot make a computer
that is as intelligent as a human in all aspects. However, we do have many successful applications. In some
cases, the computer equipped with AI technology can be even more intelligent than us. The Deep Blue
system which defeated the world chess champion is a well-know example.
The main research topics in AI include: problem solving, reasoning, planning, natural language
understanding, computer vision, automatic programming, machine learning, and so on. Of course, these
topics are closely related with each other. For example, the knowledge acquired through learning can be
used both for problem solving and for reasoning. In fact, the skill for problem solving itself should be
acquired through learning. Also, methods for problem solving are useful both for reasoning and planning.
Further, both natural language understanding and computer vision can be solved using methods developed
in the field of pattern recognition.
In this course, we will study the most fundamental knowledge for understanding AI. We will introduce
some basic search algorithms for problem solving; knowledge representation and reasoning; pattern
recognition; fuzzy logic; and neural networks.
Course Learning Outcome :
After completing the course, the student shall be able to:
1. Describe mile stones of AI and relate them to computer science as well as other fields
2. Implement software that can use most common AI-problems
3. Define the size and characteristics of a search space for a given problem and suggest suitable AI
algorithm and representation
4. Successfully apply AI algorithms to problem solving
Lab Compements :
The lab component of this course will provide Prologue exercise to develop different applications that
willcover different aspects of this course. The required software for this course is:
- Prologue: is a logic programming language. It has important role in artificial intelligence. Website:
Télécharger SWI-Prolog pour Windows, Mac, Linux - Telecharger.com (01net.com)
Grading and Evaluation Criteria :
Your course grade will be calculated as follows :

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Course syllabus
Academic Year (2023-2024)
Réf : GES-IMP-34
Indice : 01
Date :11/07/2023
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Item
Weight
(%)
Mid Exam
20
Problem sets (individual/group coursework)
10
Lab
20
Final Exam
20
Work Courses Outline :
Work
Dates
Topics
Chapte
r
Lab
Practice/e
xercices
Course
work
1
Logic foundation:
 Predicate logic
 Proposition logic
1
2
IA:
Search-based problem solving:
 Problem formulaon
 width rst
 depth of approach
 limited depth
 iterave limited depth
 best-rst search
 hill climbing
 A* algorithm, heuriscs
 beam search
 simulated annealing search
 Constraint sasfacon and search
(CSP)
 Strategic games and search: min-
max and alpha-beta
2
3
Expert systems:
 Knowledge base: fact base, rule
base
3

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Course syllabus
Academic Year (2023-2024)
Réf : GES-IMP-34
Indice : 01
Date :11/07/2023
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 Inference: forward, backward and
mixed chaining
4
Prologue:
 Basic concepts
 Relationships
 Solving constraint systems
 Trees, tuples, strings and lists
 Numerical constraints
 Predefined rules and external
procedures
4
Homework Assignemts/Projects Instructions :
All assignments must be completed and handled in on time at the beginning of class. Work must be
complete. I will not accept a partially completed assignment. Late work
Will be accepted on a case-by-case basis only.Your work must be own. Cheating will result in a
grade of 0 for the applicable assignment; further disciplinary action, including assigning a failing
grade (F) for the entire course, may also be discussed with the instructor in advance.must
Assignments must be printed out (when appropriate) and properly identified. Each printout include:
 Your Name.
 The Assignment and /or File Name.
Makerup :
 Homework: No makeup
 Midterm and final exam: Only if valid excuse is available and approved by the vice dean
of academic affairs.
 The markeup exams will be tougher than regular exams.
Instructors Policy and Academic Intergrity :
 Students are required to attend every class. Please check attendance policy at the end of
this syllabus.
 Students are expected to treat the classroom as a professianel environnement and treat
students and faculty with respect. At a minimum, i axpect you to treat each other politely
and withrespect. This includes turning off all cell phones, participating in class, and
arriving in a timely manner.Please remmember that personal conversation during lecture
are distracting to uour fellow students. Collaboration on a project is an exception, of
course.
 Stidents are expected to observe academic integrity. Cheating of any type will not be
tolerated. Students will submit their own work, if other people words are used, proper
bibliographic citation is required.

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Course syllabus
Academic Year (2023-2024)
Réf : GES-IMP-34
Indice : 01
Date :11/07/2023
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 Students will not take part in any unethical activity to improve or maintain their academic
standing. This includes but not limited to, cheating, copying, and plagiarizing. These
unethical activates will lead to a grade of «F» in the course.
 Coping an assignment from another student in this class will lead to an automatic failure
for this course and to a disciplinary action. Allowing another student to copy one’s work
will be treated as an act of academic dishonesty, leading to the same penalty as copying.