Distributed Agents, Robotics, Operations Research, Interaction, Decision Making (ANDROIDE)
The ANDROIDE course 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; in particular, it addresses all aspects related to "problem-solving" that economic professionals must face, as well as those related to the implementation of intelligent interaction processes, whether with a human user (for example, to acquire information relevant to problem- solving) or between autonomous entities, such as artificial agents or robots.
The current boom in artificial intelligence, decision support and robotics tools calls for the training of experts who can master a wide range of techniques, both symbolic and numerical, and who are able to propose innovative solutions in their professional environment, whether academic or industrial. The objective of the course is to train specialists in ICST (Information and Communication Sciences and Technologies), enabling them to master the concepts, models and tools (particularly algorithmic) of these themes.
Objectives
The pedagogical objective of the Androide course is to provide fundamental knowledge in the following areas
- interactive environments: virtual environments, human-computer interaction, serious games, video games, e-learning, information systems
- decision: decision theory, preference modeling and learning, multi-objective or multi-agent combinatorial optimization, Bayesian networks
- Robotics and intelligent systems: agent and autonomous robot, multi-agent systems, machine learning
- Operational research: mathematical programming, optimization and complexity, graphs and scheduling
Opportunities
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,
- Major web players and software publishers,
- Large industrial groups: transport, banking, energy, etc.
- Consulting firms.
Opportunities in the world of research and teaching:
- PhD in France or abroad,
- Public, private or mixed research (CIFRE theses).
Program
First year (M1 - S1)
5 UEs among the following UEs:
Acronym | Title | Person(s) in charge | ECTS | Course | |
MOGPL | Modeling, Optimization, Graphs, and Linear Programming | Patrice Perny | 6 | ANDROIDE | Mandatory |
LRC | Logic and Knowledge Representations | Jean-Gabriel Ganascia, Nicolas Maudet | 6 | ANDROIDE/DAC | Mandatory |
MAPSI | Probabilistic and Statistical Models and Algorithms for Computer Science | 6 | DAC/IMA | Highly recommended | |
COMPLEX | Complexity, Probabilistic and Approximate Algorithms | 6 | SFPN | Highly recommended | |
IL | Software Engineering | 6 | STL | Recommended | |
AAGB | Introduction to biology and algorithms on trees, and graphs in bioinformatics | 6 | BIM | Recommended | |
MLBDA | Advanced Database Models and Languages | 6 | DAC | Recommended | |
BIMA | Basics of Image Processing | 6 | IMA | Recommended | |
MODEL | 6 | SFPN | Recommended | ||
PSCR | Concurrent and Distributed System Programming | 6 | SAR | Recommended | |
ALGAV | Advanced Algorithms | 6 | STL | Recommended | |
DLP | Development of Programming Languages | 6 | STL | Recommended |
Second semester (M1 - S2)
5 UEs among the following UEs. P-ANDROID, RA and English are mandatory. You must then choose exactly 3 UEs among those marked "Complementary", including at least 2 UEs related to Androides that are "Complementary".
Acronym | Title | Person(s) in charge | ECTS | Course | |
PANDROIDE | ANDROIDE project | Nicolas Bredeche, Nicolas Maudet | 6 | ANDROIDE | Mandatory |
English | English | 3 | Dept. Langues | Mandatory | |
RA | Robotics and Learning | Olivier Sigaud | 3 | ANDROIDE | Mandatory |
RP | Problem Solving | Evripidis Bampis | 6 | ANDROIDE | Complementary |
FoSyMa | Foundations of Multiagents Systes | Aurélie Beynier | 6 | ANDROIDE | Complementary |
IHM | Human-Computer Interaction | Gilles Bailly | 6 | ANDROIDE | Complementary |
DJ | Decision and Games | Pierre-Henri Wuillemin | 6 | ANDROIDE | Complementary |
IAMSI | Artificial Intelligence and Symbolic Information Handling | 6 | DAC | Complementary | |
ML | Machine Learning | 6 | DAC | Complementary |
First semester (M2 - S1)
During this semester, there are 5 UE to choose from the table below.
Acronym | Title | Person(s) in charge | ECTS | Course |
COCOMA | Multiagent Coordination and Consensus: Models, Algorithms, Protocols | Vincent Corruble | 6 | ANDROIDE |
MAOA | Scheduling Models, Algorithms and Applications | Fanny Pascual | 6 | ANDROIDE |
EVHI | Highly Interactive Virtual Environments | Vanda Luengo | 6 | ANDROIDE |
MADI | Models and Algorithms for Decision in Uncertainty | Pierre-Henri Wuillemin | 6 | ANDROIDE |
MOSIMA | Multiagent Modeling and Simulation | Jean-Daniel Kant | 6 | ANDROIDE |
MADMC | Models and Algorithms for Multicriteria and Collective Decision- Making | Olivier Spanjaard | 6 | ANDROIDE |
AOTJ | Algorithms for Optimization and Game Theory | Bruno Escoffier | 6 | ANDROIDE |
ISG | Serious Games Engineering | Amel Yessad | 6 | ANDROIDE |
IAR | AI for Robotics | Nicolas Bredeche | 6 | ANDROIDE |
Second semester (M2 - S2)
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,
- 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.
Target audience and prerequisites
This specialization is aimed at scientific students with a good knowledge of computer science and/or mathematics applied to computer science. 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.
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. Java or C++) and, on the other hand, a strong grasp of basic mathematics (logic, algebra, analysis, probability, ...).
Contacts
Responsible for the course
- Aurélie Beynier - aurelie.beynier@sorbonne-universite.fr
- Olivier Spanjaard - olivier.spanjaard@lip6.fr
Secretaries
sciences-master-info-androide@sorbonne-universite.fr