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Talking to Strangers: Zero-Shot Emergent Communication
Marie Ossenkopf · Angelos Filos · Abhinav Gupta · Michael Noukhovitch · Angeliki Lazaridou · Jakob Foerster · Kalesha Bullard · Rahma Chaabouni · Eugene Kharitonov · Roberto Dessì

Sat Dec 12 07:00 AM -- 02:10 PM (PST) @
Event URL: https://sites.google.com/view/emecom2020/home »

Communication is one of the most impressive human abilities but historically it has been studied in machine learning mainly on confined datasets of natural language. Thanks to deep RL, emergent communication can now be studied in complex multi-agent scenarios.

Three previous successful workshops (2017-2019) have gathered the community to discuss how, when, and to what end communication emerges, producing research later published at top ML venues (e.g., ICLR, ICML, AAAI). However, many approaches to studying emergent communication rely on extensive amounts of shared training time. Our question is: Can we do that faster?

Humans interact with strangers on a daily basis. They possess a basic shared protocol, but a huge partition is nevertheless defined by the context. Humans are capable of adapting their shared protocol to ever new situations and general AI would need this capability too.

We want to explore the possibilities for artificial agents of evolving ad hoc communication spontaneously, by interacting with strangers. Since humans excel on this task, we want to start by having the participants of the workshop take the role of their agents and develop their own bots for an interactive game. This will illuminate the necessities of zero-shot communication learning in a practical way and form a base of understanding to build algorithms upon. The participants will be split into groups and will have one hour to develop their bots. Then, a round-robin tournament will follow, where bots will play an iterated zero-shot communication game with other teams’ bots.

This interactive approach is especially aimed at the defined NeurIPS workshop goals to clarify questions for a subfield or application area and to crystallize common problems. It condenses our experience from former workshops on how workshop design can facilitate cooperation and progress in the field. We also believe that this will maximize the interactions and exchange of ideas between our community.

Author Information

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.

Angelos Filos (University of Oxford)
Abhinav Gupta (Mila)
Michael Noukhovitch (Mila (Université de Montréal))

Master's student at MILA supervised by Aaron Courville and co-supervised by Yoshua Bengio

Angeliki Lazaridou (DeepMind)
Jakob Foerster (Facebook AI Research)

Jakob Foerster received a CIFAR AI chair in 2019 and is starting as an Assistant Professor at the University of Toronto and the Vector Institute in the academic year 20/21. During his PhD at the University of Oxford, he helped bring deep multi-agent reinforcement learning to the forefront of AI research and interned at Google Brain, OpenAI, and DeepMind. He has since been working as a research scientist at Facebook AI Research in California, where he will continue advancing the field up to his move to Toronto. He was the lead organizer of the first Emergent Communication (EmeCom) workshop at NeurIPS in 2017, which he has helped organize ever since.

Kalesha Bullard (Facebook AI Research)
Rahma Chaabouni (FAIR/ENS)
Eugene Kharitonov (Facebook AI Research)
Roberto Dessì (Facebook AI / Universitat Pompeu Fabra)

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