Abstract
Interactions between autonomous agents (humans and software) are necessary to increase the system’s awareness, support agents’ decision-making abilities and subsequently reduce the risks of failure. The challenge, however, is to formulate a mechanism that specifies when an agent or a human should take the initiative to interact. In this paper, we propose a Situation Awareness Assessment (SAA) model of autonomy adjustment with situation awareness capabilities in a decentralized environment. The SAA model systematizes the interactions to assist agents’ decision-making and improve the systems’ performance. The model inspects if an agent has the required awareness of a situation to be satisfactorily autonomous, otherwise, it intervenes the agent with feedback about the situation. An example scenario demonstrates the SAA ability to facilitate improved autonomous behavior in agents.
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Mostafa, S.A., Ahmad, M.S., Tang, A.Y.C., Ahmad, A., Annamalai, M., Mustapha, A. (2014). Agent’s Autonomy Adjustment via Situation Awareness. In: Nguyen, N.T., Attachoo, B., Trawiński, B., Somboonviwat, K. (eds) Intelligent Information and Database Systems. ACIIDS 2014. Lecture Notes in Computer Science(), vol 8397. Springer, Cham. https://doi.org/10.1007/978-3-319-05476-6_45
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DOI: https://doi.org/10.1007/978-3-319-05476-6_45
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