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Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
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TY - GEN
T1 - It Is Among Us: Identifying Adversaries in Ad-hoc Domains Using Q-valued Bayesian Estimations
AU - do Carmo Alves, Matheus Aparecido
AU - Varma, Amokh
AU - Soriano Marcolino, Leandro
AU - Elkhatib, Yehia
N1 - Conference code: 23
PY - 2023/12/21
Y1 - 2023/12/21
N2 - Ad-hoc teamwork models are crucial for solving distributed tasks in environments with unknown teammates. In order to improve performance, agents may collaborate in the same environment, trusting each other and exchanging information. However, what happens if there is an impostor among the team? In this paper, we present BAE, a novel and efficient framework for online planning and estimation within ad-hoc teamwork domains where there is an adversarial agent disguised as a teammate. Our approach considers the identification of the impostor through a process we term ``Q-valued Bayesian Estimation''. BAE can identify the adversary at the same time the agent performs ad-hoc estimation in order to improve coordination. Our results show that BAE has superior accuracy and faster reasoning capabilities in comparison to the state-of-the-art.
AB - Ad-hoc teamwork models are crucial for solving distributed tasks in environments with unknown teammates. In order to improve performance, agents may collaborate in the same environment, trusting each other and exchanging information. However, what happens if there is an impostor among the team? In this paper, we present BAE, a novel and efficient framework for online planning and estimation within ad-hoc teamwork domains where there is an adversarial agent disguised as a teammate. Our approach considers the identification of the impostor through a process we term ``Q-valued Bayesian Estimation''. BAE can identify the adversary at the same time the agent performs ad-hoc estimation in order to improve coordination. Our results show that BAE has superior accuracy and faster reasoning capabilities in comparison to the state-of-the-art.
KW - Adversarial Detection
KW - Ad-hoc Teamwork
KW - Online Planning
M3 - Conference contribution/Paper
BT - Proc. of the 23rd International Conference on Autonomous Agents and Multiagent Systems
PB - IFAAMAS
T2 - The 23rd International Conference on Autonomous Agents and Multi-Agent Systems
Y2 - 6 May 2024 through 10 May 2024
ER -