Teamwork with Limited Knowledge of Teammates

Author:

Barrett Samuel,Stone Peter,Kraus Sarit,Rosenfeld Avi

Abstract

While great strides have been made in multiagent teamwork, existing approaches typically assume extensive information exists about teammates and how to coordinate actions. This paper addresses how robust teamwork can still be created even if limited or no information exists about a specific group of teammates, as in the ad hoc teamwork scenario. The main contribution of this paper is the first empirical evaluation of an agent cooperating with teammates not created by the authors, where the agent is not provided expert knowledge of its teammates. For this purpose, we develop a general-purpose teammate modeling method and test the resulting ad hoc team agent's ability to collaborate with more than 40 unknown teams of agents to accomplish a benchmark task. These agents were designed by people other than the authors without these designers planning for the ad hoc teamwork setting. A secondary contribution of the paper is a new transfer learning algorithm, TwoStageTransfer, that can improve results when the ad hoc team agent does have some limited observations of its current teammates.

Publisher

Association for the Advancement of Artificial Intelligence (AAAI)

Subject

General Medicine

Cited by 6 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Empirically Understanding the Potential Impacts and Process of Social Influence in Human-AI Teams;Proceedings of the ACM on Human-Computer Interaction;2024-04-17

2. Leveraging Fitness Critics To Learn Robust Teamwork;Proceedings of the Genetic and Evolutionary Computation Conference;2023-07-12

3. Knowledge-based Reasoning and Learning under Partial Observability in Ad Hoc Teamwork;Theory and Practice of Logic Programming;2023-06-26

4. Real-Time Decentralized Navigation of Nonholonomic Agents Using Shifted Yielding Areas;2023 IEEE International Conference on Robotics and Automation (ICRA);2023-05-29

5. Explanation and Knowledge Acquisition in Ad Hoc Teamwork;Lecture Notes in Computer Science;2023

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