Too many cooks: Bayesian inference for coordinating multi-agent
collaboration

Too many cooks: Bayesian inference for coordinating multi-agent collaboration

26 March 2020

David C. Parkes

Max Kleiman-Weiner

Papers citing "Too many cooks: Bayesian inference for coordinating multi-agent collaboration"

11 / 11 papers shown

Title
Implicitly Aligning Humans and Autonomous Agents through Shared Task Abstractions Stéphane Aroca-Ouellette Miguel Aroca-Ouellette K. Wense A. Roncone 39 0 0 07 May 2025
TiZero: Mastering Multi-Agent Football with Curriculum Learning and Self-Play Fanqing Lin Shiyu Huang Tim Pearce Wenze Chen Weijuan Tu 26 17 0 15 Feb 2023
Melting Pot 2.0 J. Agapiou A. Vezhnevets Edgar A. Duénez-Guzmán Jayd Matyas Yiran Mao ... Sukhdeep Singh Julia Haas Igor Mordatch D. Mobbs Joel Z Leibo 30 31 0 24 Nov 2022
Optimal Behavior Prior: Data-Efficient Human Models for Improved Human-AI Collaboration Mesut Yang Micah Carroll Anca Dragan 32 13 0 03 Nov 2022
A Cognitive Framework for Delegation Between Error-Prone AI and Human Agents Andrew Fuchs A. Passarella M. Conti 20 7 0 06 Apr 2022
Conditional Imitation Learning for Multi-Agent Games Andy Shih Stefano Ermon Dorsa Sadigh 32 11 0 05 Jan 2022
Autonomous Reinforcement Learning: Formalism and Benchmarking Archit Sharma Kelvin Xu Nikhil Sardana Abhishek Gupta Karol Hausman Sergey Levine Chelsea Finn OffRL 41 26 0 17 Dec 2021
Collaborating with Humans without Human Data D. Strouse Kevin R. McKee M. Botvinick Edward Hughes Richard Everett 124 161 0 15 Oct 2021
On the Critical Role of Conventions in Adaptive Human-AI Collaboration Andy Shih Arjun Sawhney J. Kondic Stefano Ermon Dorsa Sadigh 36 37 0 07 Apr 2021
Expected Value of Communication for Planning in Ad Hoc Teamwork William Macke Reuth Mirsky Peter Stone 37 25 0 01 Mar 2021
Building machines that adapt and compute like brains Brenden Lake J. Tenenbaum AI4CE FedML NAI AILaw 254 890 0 11 Nov 2017