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Research activities: Optimal decision making under uncertainty
The optimal decision making under uncertainty research group in A&O/TAO elaborates on the expertise gained with the world level computer-Go player MoGo, aimed at advances in reinforcement learning and noisy optimization. The motivating applications lie in the domains of energy management and games.

  Learning and Optimization

Joint Inria project teams

Research highlights

Contracts & grants

Software & patents



Ph.D. dissertations & Faculty habilitations

Research activities
° 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
° Distributed algorithms
° Engineering of interactive systems
° 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
° Massively distributed algorithms for complex data
° Mediated collaboration
° Multi-hop wireless networks