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- 84Artificial Intelligence
- 22Machine Learning
- 21Game theory
- 10Computer Games
- 10Reinforcement Learning
- 8Planning
Author / Creator / Contributor
- 4Müller, Martin
- 3Bowling, Michael
- 3Johanson, Michael
- 3Lanctot, Marc
- 3Mueller, Martin
- 3Zinkevich, Martin
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- 65Graduate and Postdoctoral Studies (GPS), Faculty of
- 65Graduate and Postdoctoral Studies (GPS), Faculty of/Theses and Dissertations
- 21Computing Science, Department of
- 21Computing Science, Department of/Technical Reports (Computing Science)
- 4WISEST Summer Research Program
- 4WISEST Summer Research Program/WISEST Research Posters
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Fall 2015
Extensive-form games are a powerful framework for modeling sequential multi-agent interactions. In extensive-form games with imperfect information, Nash equilibria are generally used as a solution concept, but computing a Nash equilibrium can be intractable in large games. Instead, a variety of...
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{Multi-Agent Deep Reinforcement Learning for Autonomous Energy Coordination in Demand Response Methods for Residential Distribution Networks
DownloadFall 2023
In the field of collaborative learning and decision-making, this thesis aims to explore the effects of individual and joint rewards on the performance and coordination of agents in complex environments. The research objectives encompass two main aspects: firstly, to determine the objective...
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