This research group emerged in A&O/TAO at the crossroad of two perspectives. Firstly, the design of new criteria is at the core of machine learning and optimization, aimed at statistical consistency and computational efficiency.
Secondly, the design of autonomous cognitive systems also involves the definition of intrinsic motivations, or embedded criteria, with applications spanning from robotics to autonomic computing, traffic modelling and serious games.


Groups
  Learning and Optimization

Joint Inria project teams


Research highlights


Contracts & grants


Software & patents


Collaborations


Members


Ph.D. dissertations & Faculty habilitations

° Algorithm control and hyper-parameter tuning
° Algorithms for networked systems
° Automated Proof, SMT and Applications
° Automated Reasoning
° Combinatorics
° Compilation and code optimization
° Data-Centric Languages and Systems
° Deductive Verification of Programs
° Digital Fabrication
° Distributed algorithms
° Distributed Design
° Engineering of interactive systems
° Fab lab
° Formal Model-Based Testing
° Formalisation and Proof of Numerical Programs
° Formalisation of (Specification and Programming) Languages in Proof Assistants
° Generative design methods
° Graph Theory
° Green networks
° Heterogeneous Wireless Networks
° High-performance computing
° Human-Computer Interaction
° Integration of Data and Knowledge
° Interaction and visualization paradigms
° Large scale modelling