Abstract
Managing autonomy in a dynamic interactive system that contains a mix of human and software agent intelligence is a challenging task. In such systems, giving an agent a complete control over its autonomy is a risky practice while manually setting the agent’s autonomy level is an inefficient approach. This paper addresses this issue via formulating a Situation Awareness Assessment (SAA) technique to assist in determining an appropriate agents’ operational state. We propose four operational states of agents’ execution cycles; proceed, halt, block and terminate, each of which is determined based on the agents’ performance. We apply the SAA technique in a proposed Layered Adjustable Autonomy (LAA) model. The LAA conceptualizes autonomy as a spectrum and is constructed in a layered structure. The SAA and the LAA notions are applicable to humans’ and agents’ collaborative environment. We provide an experimental scenario to test and validate the proposed notions in a real-time application.
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Mostafa, S.A., Ahmad, M.S., Annamalai, M., Ahmad, A., Gunasekaran, S.S. (2015). Formulating Dynamic Agents’ Operational State via Situation Awareness Assessment. In: El-Alfy, ES., Thampi, S., Takagi, H., Piramuthu, S., Hanne, T. (eds) Advances in Intelligent Informatics. Advances in Intelligent Systems and Computing, vol 320. Springer, Cham. https://doi.org/10.1007/978-3-319-11218-3_49
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DOI: https://doi.org/10.1007/978-3-319-11218-3_49
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-11217-6
Online ISBN: 978-3-319-11218-3
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