Daniel Bloembergen
- Full Name
- Dr. D. Bloembergen
- Function(s)
- Researcher
- Daniel.Bloembergen@cwi.nl
- Telephone
- +31 20 592 4119
- Room
- M360
- Department(s)
- Intelligent and Autonomous Systems
- Homepage
- http://www.flowermountains.nl
Biography
I am a researcher at the Intelligent and Autonomous Systems group at Centrum Wiskunde & Informatica (CWI, the national research institute for mathematics and computer science). Previously I held a position as Postdoctoral Research Associate at the Department of Computer Science, University of Liverpool, UK. I did my PhD research at Maastricht University, where I graduated in May 2015.Research
My research focus is on multi-agent learning, especially reinforcement learning. I am interested in investigating how multiple learning agents interact and influence each other, what kind of global system dynamics arise, and how desired behaviour can be obtained by modifying the learning algorithms used. The settings I look at range from one-on-one interactions (e.g. games) to small groups (e.g. multi-agent coordination) and large communities (e.g. interactions in social networks).
Publications
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Santos, F.P, & Bloembergen, D. (2019). Fairness in multiplayer Ultimatum Games through moderate Responder selection. In Proceedings of the Artificial Life Conference 2019 (pp. 187–194). doi:10.1162/isal_a_00160
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Collenette, J, Atkinson, K, Bloembergen, D, & Tuyls, K. (2019). Stability of Human-Inspired Agent Societies. In Proceedings of the International Conference on Autonomous Agents and Multiagent Systems (pp. 1889–1891).
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Klima, R, Bloembergen, D, Kaisers, M, & Tuyls, K. (2019). Robust Temporal Difference Learning for Critical Domains. In Proceedings of the International Conference on Autonomous Agents and Multiagent Systems (pp. 350–358).
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Bloembergen, D, & Santos, F.P. (Fernando). (2019). Moderate Responder Committees Maximize Fairness in (NxM)-Person Ultimatum Games.
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Bakker, J, Hammond, A, Bloembergen, D, & Baarslag, T. (2019). RLBOA: A Modular Reinforcement Learning Framework for Autonomous Negotiating Agents. In Proceedings of the International Conference on Autonomous Agents and Multiagent Systems (pp. 260–268).
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Bloembergen, D, Grossi, D, & Lackner, M. (2019). On rational delegations in liquid democracy. In Proceedings of the AAAI Conference on Artificial Intelligence (pp. 1796–1803).
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Collenette, J, Atkinson, K, Bloembergen, D, & Tuyls, K. (2018). On the role of mobility and interaction topologies in social dilemmas. In ALIFE 2018 - Proceedings of the artificial life conference 2018 (pp. 477–484). doi:10.1162/isal_a_00088
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Palmer, G, Tuyls, K, Bloembergen, D, & Savani, R. (2018). Lenient multi-agent deep reinforcement learning. In AAMAS '18 - Proceedings of the 17th International Conference on Autonomous Agents and MultiAgent Systems (pp. 443–451).
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Klima, R, Bloembergen, D, Savani, R, Tuyls, K, Wittig, A, Sapera, A, & Izzo, D. (2018). Space debris removal: Learning to cooperate and the price of anarchy. Frontiers in Robotics and AI, 5(JUN). doi:10.3389/frobt.2018.00054
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Klima, R, Bloembergen, D, Kaisers, M, & Tuyls, K. (2018). Learning robust policies when losing control. In Proceedings of Adaptive and Learning Agents (ALA) Workshop, 2018.
Current projects with external funding
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Flexible Assets Bid Across Markets (FABAM)