Dr. F.A. (Frans) Oliehoek

Dr. F.A. (Frans) Oliehoek

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Ruimte: 29.02.320

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For more information, please see my personal webpage.

Dr. Frans A. Oliehoek is Associate Professor at Delft University of Technology, where he is a leader of the sequential decision making group, a scientific director of the Mercury machine learning lab, and director and co-founder of the ELLIS Unit Delft. He received his Ph.D. in Computer Science (2010) from the University of Amsterdam (UvA), and held  positions at various universities including MIT, Maastricht University and the University of Liverpool.  Frans' research interests revolve around intelligent systems that learn about their environment via interaction, building on techniques from machine learning, AI and game theory. He has served as PC/SPC/AC at top-tier venues in AI and machine learning, and currently serves as associate editor for JAIR and AIJ. He is a Senior Member of AAAI, Fellow of ELLIS, and was awarded a number of personal research grants, including a prestigious ERC Starting Grant.

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Onderzoeksinteresses

 

My main research interests lie in what I call interactive learning and decision making: the intersection of AI, machine learning and game theory that focuses on an intelligent agent that interacts with a complex world. My long term vision is the construction of a collaborative AI scientist. In the short term, I try to generate fundamental knowledge about algorithms and models for learning complex tasks. Specifically, I believe that agents need models to support intelligent decision making. Learning such models is difficult, and given that our world constantly changes, we cannot assume that  agents will ever learn perfect models. Instead, we need to endow them with the capability to learn these models online, i.e., while interacting with their environments: they need to be able to use imperfect models, reason about the uncertainty in their predictions, and actively learn to improve these models (balancing task rewards and knowledge gathering). In addition, I think about how such abstract models might be applied to a variety of real-world tasks such as collaboration in multi-robot or human-AI systems, optimization of traffic control systems, intelligent e-commerce agents, etc.

 

 

 

For more information about my research, look here.

 

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Ruimte: 29.02.320