Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/144311
Title: AATEAM : achieving the ad hoc teamwork by employing the attention mechanism
Authors: Chen, Shuo
Andrejczuk, Ewa
Cao, Zhiguang
Zhang, Jie
Keywords: Engineering::Electrical and electronic engineering
Issue Date: 2020
Source: Chen, S., Andrejczuk, E., Cao, Z., & Zhang, J. (2020). AATEAM : achieving the ad hoc teamwork by employing the attention mechanism. Proceedings of the AAAI Conference on Artificial Intelligence, 34(5). doi:10.1609/aaai.v34i05.6196
Abstract: In the ad hoc teamwork setting, a team of agents needs to perform a task without prior coordination. The most advanced approach learns policies based on previous experiences and reuses one of the policies to interact with new teammates. However, the selected policy in many cases is sub-optimal. Switching between policies to adapt to new teammates’ behaviour takes time, which threatens the successful performance of a task. In this paper, we propose AATEAM – a method that uses the attention-based neural networks to cope with new teammates’ behaviour in real-time. We train one attention network per teammate type. The attention networks learn both to extract the temporal correlations from the sequence of states (i.e. contexts) and the mapping from contexts to actions. Each attention network also learns to predict a future state given the current context and its output action. The prediction accuracies help to determine which actions the ad hoc agent should take. We perform extensive experiments to show the effectiveness of our method.
URI: https://hdl.handle.net/10356/144311
DOI: 10.1609/aaai.v34i05.6196
Rights: © 2020 Association for the Advancement of Artificial Intelligence (AAAI). All rights reserved. This paper was published in Proceedings of the AAAI Conference on Artificial Intelligence and is made available with permission of Association for the Advancement of Artificial Intelligence (AAAI).
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Conference Papers

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