Michael Kaisers
- Full Name
- Dr. M. Kaisers
- Function(s)
- Scientific Staff Member
- M.Kaisers@cwi.nl
- Telephone
- +31 20 592 4035
- Room
- M359
- Department(s)
- Intelligent and Autonomous Systems
- Homepage
- http://www.michaelkaisers.com
Biography
Michael Kaisers investigates strategies and mechanisms for strategic interactions with both cooperative and competitive elements, inspired by applications in energy systems, trading in markets and negotiations. He has published more than 40 research articles in computer science, on the intersection of artificial intelligence and game theory, and now leads and contributes to European joint research projects, having acquired more than 1 million Euro in funding for work on multi-agent reinforcement learning, evolutionary dynamics, and efficient flexibility allocation in smart energy systems.
Publications
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Lezama, F, Soares, J, Hernandez-Leal, P, Kaisers, M, Pinto, T, & Almeida do Vale, Z.M. (2018). Local energy markets: Paving the path towards fully transactive energy systems. IEEE Transactions on Power Systems. doi:10.1109/TPWRS.2018.2833959
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Baarslag, T, Kaisers, M, Gerding, E.H, Jonker, C.M, & Gratch, J. (2017). Computers that negotiate on our behalf: Major challenges for self-sufficient, self-directed, and interdependent negotiating agents. In Autonomous Agents and Multiagent Systems: AAMAS 2017 Workshops, Visionary Papers (pp. 143–163). doi:http:dx.doi.org/10.1007/978-3-319-71679-4_10
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Baarslag, T, Kaisers, M, Gerding, E.H, Jonker, C.M, & Gratch, J. (2017). When will negotiation agents be able to represent us? The challenges and opportunities for autonomous negotiators. In Proceedings of the Twenty-sixth International Joint Conference on Artificial Intelligence (pp. 4684–4690). doi:10.24963/ijcai.2017/653
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Hernandez-Leal, P, & Kaisers, M. (2017). Learning against sequential opponents in repeated stochastic games. In Multi-disciplinary Conference on Reinforcement Learning and Decision Making (pp. 52–56).
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Hernandez-Leal, P, & Kaisers, M. (2017). Towards a fast detection of opponents in repeated stochastic games. In Lecture Notes in Computer Science/Lecture Notes in Artificial Intelligence (pp. 239–257). doi:10.1007/978-3-319-71682-4_15
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Baarslag, T, & Kaisers, M. (2017). The Value of Information in Automated Negotiation: A Decision Model for Eliciting User Preferences. In Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems.
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Methenitis, G, Kaisers, M, & La Poutré, J.A. (2017). SLA-mechanisms for electricity trading under volatile supply and varying criticality of demand (Extended Abstract). In Proceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems (pp. 1640–1642).
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Methenitis, G, Kaisers, M, & La Poutré, J.A. (2017). SLA mechanisms for electricity trading under volatile supply and varying criticality of demand. In Proc. of the Int. Workshop on Agent- Mediated Electronic Commerce and Trading Agents Design and Analysis (AMEC/TADA).
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Baarslag, T, Kaisers, M, Gerding, E.H, Jonker, C.M, & Gratch, J. (2017). When will negotiation agents be able to represent us? The challenges and opportunities for autonomous negotiators. In Proc. of the Int. Workshop on Agent-Mediated Electronic Commerce and Trading Agents Design and Analysis (AMEC/TADA).
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Hernandez-Leal, P, & Kaisers, M. (2017). Towards a fast detection of opponents in repeated stochastic games. In Proc. of the 1st Workshop on Transfer in Reinforcement Learning (TiRL).
Current projects with external funding
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Energy loan exchange (ELE)
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Flexible Assets Bid Across Markets (FABAM)
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Demand response for grid-friendly quasi-autarkic energy cooperatives (Grid-Friends)