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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.


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  Learning and Optimization

Joint Inria project teams


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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