Program Overview

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

The AI2D program covers topics related to problem-solving, agents, decision-making, and autonomous robotics. This training aims to provide both theoretical and practical education covering all the main areas of artificial intelligence, decision, operational research, and interaction.

Objectives

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

• 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

Opportunities

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

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

Program

First Year (M1)

The first year consists of two semesters. The first semester includes:

• MOGPL: Modeling, Optimization, Graphs, and Linear Programming (6 ECTS)
• LRC: Logic and Knowledge Representations (6 ECTS)
• IREC: Introduction to research (3 ECTS)
• English (3 ECTS)
• MAPSI: Probabilistic and Statistical Models and Algorithms for Computer Science (6 ECTS)
• COMPLEX: Complexity, Probabilistic and Approximate Algorithms (6 ECTS)
• IL: Software Engineering (6 ECTS)
• AAGB: Introduction to biology and algorithms on trees, and graphs in bioinformatics (6 ECTS)
• MLBDA: Advanced Database Models and Languages (6 ECTS)
• BIMA: Basics of Image Processing (6 ECTS)
• MODEL: Calculation Models (6 ECTS)
• PSCR: Concurrent and Distributed System Programming (6 ECTS)
• ALGAV: Advanced Algorithms (6 ECTS)
• DLP: Development of Programming Languages (6 ECTS) The second semester includes:
• PAI2D: AI2D project (6 ECTS)
• AROB: Learning and Robotics (6 ECTS)
• RP: Problem Solving (6 ECTS)
• FoSyMa: Foundations of Multiagents Systems (6 ECTS)
• IHM: Human-Computer Interaction (6 ECTS)
• DJ: Decision and Games (6 ECTS)
• IAMSI: Artificial Intelligence and Symbolic Information Handling (6 ECTS)
• ML: Machine Learning (6 ECTS)

Second Year (M2)

The second year consists of two semesters. The first semester includes:

• COCOMA: Multiagent Coordination and Consensus: Models, Algorithms, Protocols (6 ECTS)
• MAOA: Scheduling Models, Algorithms and Applications (6 ECTS)
• HAII: Human Artificial Intelligence Interaction (6 ECTS)
• MADI: Models and Algorithms for Decision in Uncertainty (6 ECTS)
• MOSIMA: Multiagent Modeling and Simulation (6 ECTS)
• MADMC: Models and Algorithms for Multicriteria and Collective Decision-Making (6 ECTS)
• AOTJ: Algorithms for Optimization and Game Theory (6 ECTS)
• AI-ADAPT: AI for Adaptation of Multimodal Environments (6 ECTS)
• IAR: AI for Robotics (6 ECTS) The second semester is dedicated to an internship (company or laboratory).

Skills and Knowledge

Upon completion, the graduate will be able to:

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

Target Audience and Prerequisites

This specialization is aimed at scientific students with a good knowledge of computer science and/or applied mathematics. The prerequisites for our training are:

• general knowledge of computer science
• mastery of algorithms and programming (e.g., Python, Java or C++)
• strong grasp of basic mathematics (logic, algebra, analysis, probability, etc.)

Research Areas

The AI2D program covers various research areas, including:

• Decision
• Interactive environments
• Operational research
• Robotics and intelligent systems