Réf : GES-IMP-34 Course syllabus Indice : 01 Date :11/07/2023 Academic Year (2023-2024) Page 1/1 Course Syllabus IA: Artificial intelligence Academic Year(2023-2024)-Second Semester Instructor : Name : Ben Fradj HAJER Contact inf : [email protected] Phone : 28983214 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). 1 Réf : GES-IMP-34 Course syllabus Academic Year (2023-2024) 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 : 2 Réf : GES-IMP-34 Course syllabus Indice : 01 Date :11/07/2023 Academic Year (2023-2024) Page 3/1 Item Weight (%) Mid Exam 20 Problem sets (individual/group coursework) 10 Lab 20 Final Exam 20 Work Courses Outline : Work Dates 1 Topics Logic foundation: Predicate logic 2 Chapte r Lab Practice/e xercices Course work 1 Proposition logic 2 IA: Search-based problem solving: 3 Problem formulation width first depth of approach limited depth iterative limited depth best-first search hill climbing A* algorithm, heuristics beam search simulated annealing search Constraint satisfaction and search (CSP) Strategic games and search: minmax and alpha-beta Expert systems: Knowledge base: fact base, rule base 3 3 Réf : GES-IMP-34 Course syllabus Indice : 01 Date :11/07/2023 Academic Year (2023-2024) Page 4/1 4 Inference: forward, backward and mixed chaining 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. 4 Réf : GES-IMP-34 Course syllabus Academic Year (2023-2024) Indice : 01 Date :11/07/2023 Page 5/1 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. 5
