Authors

* External authors

Venue

Date

Share

A Penny for Your Thoughts: The Value of Communication in Ad Hoc Teamwork

Reuth Mirsky*

William Macke*

Andy Wang*

Harel Yedidsion*

Peter Stone

* External authors

IJCAI-2020

2021

Abstract

In ad hoc teamwork, multiple agents need to collaborate without having knowledge about their teammates or their plans a priori. A common assumption in this research area is that the agents cannot communicate. However, just as two random people may speak the same language, autonomous teammates may also happen to share a communication protocol. This paper considers how such a shared protocol can be leveraged, introducing a means to reason about Communication in Ad Hoc Teamwork (CAT). The goal of this work is enabling improved ad hoc teamwork by judiciously leveraging the ability of the team to communicate. We situate our study within a novel CAT scenario, involving tasks with multiple steps, where teammates' plans are unveiled over time. In this context, the paper proposes methods to reason about the timing and value of communication and introduces an algorithm for an ad hoc agent to leverage these methods. Finally, we introduces a new multiagent domain, the tool fetching domain, and we study how varying this domain's properties affects the usefulness of communication. Empirical results show the benefits of explicit reasoning about communication content and timing in ad hoc teamwork.

Related Publications

Benchmarking Reinforcement Learning Techniques for Autonomous Navigation

ICRA, 2023
Zifan Xu*, Bo Liu*, Xuesu Xiao*, Anirudh Nair*, Peter Stone

Deep reinforcement learning (RL) has broughtmany successes for autonomous robot navigation. However,there still exists important limitations that prevent real-worlduse of RL-based navigation systems. For example, most learningapproaches lack safety guarantees; and learned na…

Learning Perceptual Hallucination for Multi-Robot Navigation in Narrow Hallways

ICRA, 2023
Jin-Soo Park*, Xuesu Xiao*, Garrett Warnell*, Harel Yedidsion*, Peter Stone

While current systems for autonomous robot navigation can produce safe and efficient motion plans in static environments, they usually generate suboptimal behaviors when multiple robots must navigate together in confined spaces. For example, when two robots meet each other i…

A Domain-Agnostic Approach for Characterization of Lifelong Learning Systems

Neural Networks, 2023
Megan M. Baker*, Alexander New*, Mario Aguilar-Simon*, Ziad Al-Halah*, Sébastien M. R. Arnold*, Ese Ben-Iwhiwhu*, Andrew P. Brna*, Ethan Brooks*, Ryan C. Brown*, Zachary Daniels*, Anurag Daram*, Fabien Delattre*, Ryan Dellana*, Eric Eaton*, Haotian Fu*, Kristen Grauman*, Jesse Hostetler*, Shariq Iqbal*, Cassandra Kent*, Nicholas Ketz*, Soheil Kolouri*, George Konidaris*, Dhireesha Kudithipudi*, Seungwon Lee*, Michael L. Littman*, Sandeep Madireddy*, Jorge A. Mendez*, Eric Q. Nguyen*, Christine D. Piatko*, Praveen K. Pilly*, Aswin Raghavan*, Abrar Rahman*, Santhosh Kumar Ramakrishnan*, Neale Ratzlaff*, Andrea Soltoggio*, Peter Stone, Indranil Sur*, Zhipeng Tang*, Saket Tiwari*, Kyle Vedder*, Felix Wang*, Zifan Xu*, Angel Yanguas-Gil*, Harel Yedidsion*, Shangqun Yu*, Gautam K. Vallabha*

Despite the advancement of machine learning techniques in recent years, state-of-the-art systems lack robustness to “real world” events, where the input distributions and tasks encountered by the deployed systems will not be limited to the original training context, and syst…

  • HOME
  • Publications
  • A Penny for Your Thoughts: The Value of Communication in Ad Hoc Teamwork

JOIN US

Shape the Future of AI with Sony AI

We want to hear from those of you who have a strong desire
to shape the future of AI.