Machine Learning for Decision Problems, Hierarchical Representations and Controls, Preference Learning
Mail. TU Darmstadt, FB-Informatik, FG-IAS, Hochschulstr. 10, 64289 Darmstadt
Office. Room E226, Robert-Piloty-Gebaeude S2|02
As part of his PhD thesis, Riad worked with his advisors Michèle Sebag and Marc Schoenauer on reducing the expertise requirements of Policy Learning algorithms allowing uninitiated users to teach robots new tasks. They did so by proposing a learning framework (Preference-based Reinforcement Learning) where the user gives binary feedback (better/worse) to trajectories demonstrated by the robot; reducing the role of the user to that of a mere critic. He is expected during his postdoc to focus on the automatic discovery of structure in robot trajectories and to develop (hierarchical) algorithms capable of exploiting it.
Prior to his PhD, he received a diploma in Computer Engineering from Ecole Nationale Superieure d'Informatique (Algiers, Algeria) and an MSc in Artificial Intelligence and Decision from Université Pierre et Marie Curie (Paris, France).