Rethinking Approximate Value Iteration Algorithms

NAVER LABS Europe (Grenoble, France) is the biggest industrial AI research lab in France with fundamental and applied research in the fields of machine learning and optimization, computer vision, natural language processing and human robot interaction. The main area of application  is  AI for Robotics where they work closely with  NAVER LABS Korea the R&D subsidiary of NAVER, Korea’s leading internet company. NAVER LABS is responsible for creating future technology in robotics, AI, autonomous driving, 3D/HD mapping and AR.LinkedIn-Bluesky

NAVER LABS Europe

Speaker: Téo Vincent is a Ph.D. student at the Technical University of Darmstadt and at DFKI

Abstract: Approximate value iteration (AVI) is a family of algorithms for Reinforcement Learning (RL) that aims to obtain an approximation of the optimal value function. Generally, AVI algorithms implement an iterated procedure where each step consists of (i) an application of the Bellman operator and (ii) a projection step into a considered function space. The Bellman operator leverages transition samples, which strongly determine its behavior, as uninformative samples can result in negligible updates or long detours, whose detrimental effects are further exacerbated by the computationally intensive projection step. In this talk, I will present two ideas to addressing these issues. One idea is to learn an approximate version of the Bellman operator to mitigate our dependency on the data. The other idea is to consider multiple iterations of the Bellman operator at once to improve the learning of the projection step.Biography: Théo Vincent is a Ph.D. student at the Technical University of Darmstadt and at DFKI, the German Institute for Artificial Intelligence. He is currently working on off-policy Reinforcement Learning methods under the supervision of Boris Belousov and Jan Peters. Before his Ph.D., Théo graduated from MVA at ENS Paris Saclay. He also worked on Compute Vision problems in a Parisian lab, Saint-Venant lab, and a Swedish start-up, Signality. Théo did an internship in biostatistics at Harvard Medical School. This seminar is hybrid. <a href="https://hasna.gharsouli@naverlabs.com" title="https://hasna.gharsouli@naverlabs.com" target="_blank" data-msys-clicktrack="0" rel="nofollow noopener noreferrer">Please contact us</a> if you can come and meet us <a href="https://europe.naverlabs.com/contact/" title="https://europe.naverlabs.com/contact/" target="_blank" data-msys-clicktrack="0" rel="nofollow noopener noreferrer">on-site</a> or register to join us on Zoom

Rethinking Approximate Value Iteration Algorithms

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Rethinking Approximate Value Iteration Algorithms

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