Machine Learning Research Higlights

NAI Program

In the Natural Artificial Intelligence call, NWO EW awarded six research teams grants for advancing state-of-the-art AI. The NAI program has a multidisciplinary aim, and consists of research-projects that aim to strengthen the link between natural intelligence and artificial intelligence, combining insights either area to reinforce the other. The projects specifically target advances in deep learning, cognitive robotics, and models of efficient learning in brain-like structures.

The awarded projects include:

  • Learning the Fundamental Symmetries in Video Data (M. Welling (UvA) and L.P.J. van der Maaten (TUD))
  • Reward-based learning of Subroutines by Neural networks (P.R. Roelfsema (NHI) and S.M. Bohté (CWI))
  • Deep Learning for Robust Robot Control (R. Babuska (TUD) and K. Tuyls (TUD))
  • Learning to Communicate via Social and Linguistic Interaction (P.A. Vogt (UvT) and A. Alishahi (UvT))
  • Deep Spiking Vision: Better, Faster, Cheaper (S.M. Bohté (CWI) and S. Ghebreab (UvA), H.S. Scholte (UvA))
  • Decentralized UAV Control (G.C.H.E. de Croon (TUD) and H.J. Kappen (RU), K. Tuyls (TUD))