"baghiani radouane" Atelier 4 2025

This course provides an in-depth introduction to the fundamental concepts of knowledge representation and reasoning in Artificial Intelligence. It explores various approaches used to model, structure, and exploit information within intelligent systems, including non-classical logics, probabilistic reasoning, and fuzzy logic.

Special emphasis is placed on understanding how intelligent systems make decisions in complex, uncertain, or incomplete environments. Through practical examples, exercises, and interactive activities, students will learn how to design formal models and select appropriate reasoning techniques depending on the context.

The course covers key formalisms such as modal logic, default logic, and description logics, alongside major approaches to uncertain reasoning including Dempster–Shafer Theory and Bayesian Networks. Students will engage with structured exercises and guided case studies to compare these methods and understand their respective strengths, limitations, and fields of application.

This course serves as a foundational component for the development of intelligent systems and prepares students for advanced applications in artificial intelligence, data science, and decision-support systems. It is intended for 4th-year engineering students in Computer Science who have prior knowledge in logic, discrete mathematics, and basic AI concepts.

Students should have a solid foundation in the following areas before starting this course:

• Propositional and first-order logic
• Discrete mathematics (set theory, relations, graphs)
• Basic concepts of Artificial Intelligence
• Elementary probability theory

[Staff Member #1 Name]

[Biography of instructor/staff member #1 — include academic background, research interests, and relevant teaching experience.]

[Staff Member #2 Name]

[Biography of instructor/staff member #2 — include academic background, research interests, and relevant teaching experience.]

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Do I need prior programming experience?

This course focuses on formal reasoning and logic rather than programming. However, basic familiarity with logical notation and AI concepts will help you follow the material more easily.