Lecturers
Professor: Michèle Courant, DIUF, Pérolles 2, Bd de Pérolles 90, Office A408
Assistant: Vincenzo Pallotta , DIUF, Pérolles 2, Bd de Pérolles 90, Office A428
General Information
- Starting date: Tuesday March 13, 2007
- Scope: 5 ECTS (5*30 hours of personal work for students).
- Course language: French
Enrollment
- Course enrollment is mandatory. It can be achieved online at: http://www.unifr.ch/science/gestens
and then click on 'connexion' under the the heading 'Espace étudiants'
- Mailing list registration is necessary. It can be achieved online at: https://lists.unifr.ch/wws/subscribe/diuf-students-ai
- For this course, a Forum will be used to communicate additional information concerning the courses or exercises.
You can also use it for general discussions concerning the course. Registration to the forum is mandatory!
Time and Place
- Course: Tuesday, 13h15-15h00, DIUF, Pérolles 2, Bd de Pérolles 90, PER21 - B205
- Exercises / projects: Tuesday, 15h15-16h00, DIUF, Pérolles 2, Bd de Pérolles 90, PER21 - B205
- Office hours:
- Michèle Courant: <TBA>, DIUF, Pérolles 2, Bd de Pérolles 90, Office A408
- Vincenzo Pallotta: Thursday 14h00 - 16h00, DIUF, Pérolles 2, Bd de Pérolles 90, Office A428
Objectives
To study the main challenges and methodologies of artificial intelligence.
Content
Artificial intelligence (AI) is built around two objectives:
- First to model –human and animal, individual and collective intelligence– in order to understand it,
- Second to design artificial intelligence systems in order to provide assistance to humans.
It is organized in two main trends, that will be both addressed through the course:
- The classical AI approach is built on knowledge representation and knowledge exploitation. We will then study the main formalisms used for knowledge modelling (logic/relational, structured and agent-based approaches), and the main categories of problems one can solve with these formalisms (reasoning, planning, learning, dialogue,...).
- The new AI approach is based on the paradigm of emergence and self-organization. It tries to understand intelligence, and to model it, as an integral part of life. It is then characterized by its embodiement (intelligence in a body) and the fact that intelligence is situated in a physical world. Thus, this trend is also able to address intelligent behaviors like the capacity of a robot to avoid obstacles and damaging itself, to manage by itself its energy, as well as to solve a gathering task or to find its way using bio-inspired methods, like ant algorithms.
Prerequisites
Bachelor in Informatics, namely Programming (Progr. II), Algorithms (Progr. IIA).
