Training Coordination Proxy Agents

Delegating the coordination role to proxy agents can improve the overall outcome of the task at the expense of cognitive overload due to switching subtasks. Stability and commitment are characteristics of human teamwork but must not prevent the detection of better opportunities. In addition, coordin...

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Bibliographic Details
Main Authors: Abramson, M., Chao, W., Mittu, R.
Format: Conference Proceeding
Language:English
Subjects:
Chaotic communication
Communications technology
Decision making
Humans
Laboratories
Machine learning
Multiagent systems
Roads
Stability
Teamwork
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Summary:Delegating the coordination role to proxy agents can improve the overall outcome of the task at the expense of cognitive overload due to switching subtasks. Stability and commitment are characteristics of human teamwork but must not prevent the detection of better opportunities. In addition, coordination proxy agents must be trained from examples as a single agent but must interact with multiple agents. We apply machine learning techniques to the task of learning team preferences from mixed-initiative interactions and compare the outcome results of different simulated user patterns. This paper introduces a novel approach for the adjustable autonomy of coordination proxies based on the reinforcement learning of abstract actions.
ISSN:2161-4393
2161-4407
DOI:10.1109/IJCNN.2006.246690