Artificial Intelligence, Algorithms, Interaction, Decision Making (AI2D)

The pedagogical objective of the AI2D program is to provide fundamental knowledge in the following areas (in alphabetical order):

• Decision: decision theory, preference modeling and learning, multi-objective or multi-agent combinatorial optimization, Bayesian networks
• Interactive environments: virtual environments, human-computer interaction, serious games, video games, e-learning, information systems
• Operational research: mathematical programming, optimization and complexity, graphs and scheduling
• Robotics and intelligent systems: agent and autonomous robot, multi-agent systems, machine learning

This innovative teaching ensures the training of future specialists, both engineers and researchers, in a rapidly expanding field.

Opportunities in the business world:

• High-tech companies: video games, e-learning, industrial and domestic robotics,
• Large industrial groups: transport, aerospace, automotive industry, telecommunications, banking, energy, etc.
• Major web players and software publishers,
• Public institutions,
• Consulting firms.

Opportunities in the world of research and teaching:

• PhD in France or abroad,
• Public, private or mixed research (CIFRE theses),
• Companies involved in research and development.

Upon completion, the graduate will be able to:

• model optimization problems, and optimize algorithms for solving combinatorial problems and mathematical programs,
• to collect and formalize expert knowledge and build decision support systems, particularly probabilistic ones,
• to design computer tools to help a decision-maker analyze a problem or a situation and provide solutions,
• to design and develop adaptive and autonomous agents or robots,
• to design artificial intelligence algorithms for robotics, including navigation, mapping and planning, as well as learning and evolving algorithms for robot adaptation,
• to design and produce intelligent interfaces, interactive environments, video games and serious games.

This specialization is aimed at scientific students with a good knowledge of computer science and/or applied mathematics. The cohort of the first year is mainly made up of students with a bachelor's degree in computer science or mathematics (with some units in programming and algorithmic), but less typical backgrounds are also considered seriously. The second year cohort is made up of students from the first year, together with engineering students or coming from other master programs.

The prerequisites for our training are, on the one hand, to have general knowledge of computer science and a mastery of algorithms and programming (e.g. Python, Java or C++) and, on the other hand, a strong grasp of basic mathematics (logic, algebra, analysis, probability, ...).