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ORCIDThore Graepel
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Publications
- 2019
[c75]Andrea Tacchetti, H. Francis Song, Pedro A. M. Mediano, Vinícius Flores Zambaldi, János Kramár, Neil C. Rabinowitz, Thore Graepel, Matthew M. Botvinick, Peter W. Battaglia:
Relational Forward Models for Multi-Agent Learning. ICLR (Poster) 2019- 2018
- [c70]Peter Sunehag, Guy Lever, Audrunas Gruslys, Wojciech Marian Czarnecki, Vinícius Flores Zambaldi, Max Jaderberg, Marc Lanctot, Nicolas Sonnerat, Joel Z. Leibo, Karl Tuyls, Thore Graepel:
Value-Decomposition Networks For Cooperative Multi-Agent Learning Based On Team Reward. AAMAS 2018: 2085-2087 - [i15]Andrea Tacchetti, H. Francis Song, Pedro A. M. Mediano, Vinícius Flores Zambaldi, Neil C. Rabinowitz, Thore Graepel, Matthew M. Botvinick, Peter W. Battaglia:
Relational Forward Models for Multi-Agent Learning. CoRR abs/1809.11044 (2018) - 2017
- [c66]Joel Z. Leibo, Vinícius Flores Zambaldi, Marc Lanctot, Janusz Marecki, Thore Graepel:
Multi-agent Reinforcement Learning in Sequential Social Dilemmas. AAMAS 2017: 464-473 - [c65]Julien Pérolat, Joel Z. Leibo, Vinícius Flores Zambaldi, Charles Beattie, Karl Tuyls, Thore Graepel:
A multi-agent reinforcement learning model of common-pool resource appropriation. NIPS 2017: 3643-3652 - [c64]Marc Lanctot, Vinícius Flores Zambaldi, Audrunas Gruslys, Angeliki Lazaridou, Karl Tuyls, Julien Pérolat, David Silver, Thore Graepel:
A Unified Game-Theoretic Approach to Multiagent Reinforcement Learning. NIPS 2017: 4190-4203 - [i13]Joel Z. Leibo, Vinícius Flores Zambaldi, Marc Lanctot, Janusz Marecki, Thore Graepel:
Multi-agent Reinforcement Learning in Sequential Social Dilemmas. CoRR abs/1702.03037 (2017) - [i12]Peter Sunehag, Guy Lever, Audrunas Gruslys, Wojciech Marian Czarnecki, Vinícius Flores Zambaldi, Max Jaderberg, Marc Lanctot, Nicolas Sonnerat, Joel Z. Leibo, Karl Tuyls, Thore Graepel:
Value-Decomposition Networks For Cooperative Multi-Agent Learning. CoRR abs/1706.05296 (2017) - [i11]Julien Pérolat, Joel Z. Leibo, Vinícius Flores Zambaldi, Charles Beattie, Karl Tuyls, Thore Graepel:
A multi-agent reinforcement learning model of common-pool resource appropriation. CoRR abs/1707.06600 (2017) - [i10]Marc Lanctot, Vinícius Flores Zambaldi, Audrunas Gruslys, Angeliki Lazaridou, Karl Tuyls, Julien Pérolat, David Silver, Thore Graepel:
A Unified Game-Theoretic Approach to Multiagent Reinforcement Learning. CoRR abs/1711.00832 (2017)
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