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Extended Poster Session
Travis LaCroix · Marie Ossenkopf · Mina Lee · Nicole Fitzgerald · Daniela Mihai · Jonathon Hare · Ali Zaidi · Alexander Cowen-Rivers · Alana Marzoev · Eugene Kharitonov · Luyao Yuan · Tomasz Korbak · Paul Pu Liang · Yi Ren · Roberto Dessì · Peter Potash · Shangmin Guo · Tatsunori Hashimoto · Percy Liang · Julian Zubek · Zipeng Fu · Song-Chun Zhu · Adam Lerer

Sat Dec 14 11:30 AM -- 12:00 PM (PST) @

Author Information

Travis LaCroix (University of California, Irvine)
Marie Ossenkopf (University of Kassel)

Marie Ossenkopf (Uni Kassel) is a PhD student at the University of Kassel in the Distributed Systems Group supervised by Kurt Geihs. She is currently writing her thesis on architectural necessities of emergent communication, especially for multilateral agreements. She received her MSc in Automation Engineering from RWTH Aachen University in 2016 and organizes international youth exchange workshops since 2017. She was a co-organizer of the Emergent Communication workshop at NeurIPS 2019. When Does Communication Learning Need Hierarchical Multi-Agent Deep Reinforcement Learning. Ossenkopf, Marie; Jorgensen, Mackenzie; Geihs, Kurt. In: Cybernetics and Systems vol. 50, Taylor & Francis (2019), Nr. 8, pp. 672-692 Hierarchical Multi-Agent Deep Reinforcement Learning to Develop Long-Term Coordination. Ossenkopf, Marie, Mackenzie Jorgensen, and Kurt Geihs. SAC 2019.

Mina Lee (Stanford University)
Nicole Fitzgerald (Microsoft Research)
Daniela Mihai (University of Southampton)
Jonathon Hare (University of Southampton)
Ali Zaidi (Microsoft / Stanford University)
Alexander Cowen-Rivers (University College London)
Alana Marzoev (MIT)
Eugene Kharitonov (Facebook AI)
Luyao Yuan (University of California, Los Angeles)
Tomasz Korbak (Institute of Philosophy and Sociology, Polish Academy of Sciences)
Paul Pu Liang (Carnegie Mellon University)
Yi Ren (The University of Edinburgh)
Roberto Dessì (Universitat Pompeu Fabra)
Peter Potash (Microsoft Research Montreal)
Shangmin Guo (School of Informatics)
Tatsunori Hashimoto (Stanford)
Percy Liang (Stanford University)
Percy Liang

Percy Liang is an Assistant Professor of Computer Science at Stanford University (B.S. from MIT, 2004; Ph.D. from UC Berkeley, 2011). His research spans machine learning and natural language processing, with the goal of developing trustworthy agents that can communicate effectively with people and improve over time through interaction. Specific topics include question answering, dialogue, program induction, interactive learning, and reliable machine learning. His awards include the IJCAI Computers and Thought Award (2016), an NSF CAREER Award (2016), a Sloan Research Fellowship (2015), and a Microsoft Research Faculty Fellowship (2014).

Julian Zubek (University of Warsaw)
Zipeng Fu (University of California, Los Angeles)
Song-Chun Zhu (UCLA)
Adam Lerer (Facebook AI Research)

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