A dynamically adjustable autonomic agent framework

• Main Authors: Mostafa S.A., Ahmad M.S., Annamalai M., Ahmad A., Gunasekaran S.S.
• Other Authors: 37036085800
• Format: Conference paper
• Published: Springer Verlag 2023
• Subjects: adjustable autonomy; autonomous systems; autonomy analysis; decision-making; Multi-agent system (MAS); situation awareness; Software agent; Automation; Information systems; Multi agent systems; Software agents; Adjustable autonomy; Autonomous systems; Multi agent system (MAS); Situation awareness; Autonomous agents

The design and development of autonomous software agents is still a challenging task and needs further investigation. Giving an agent the maximum autonomous capabilities may not necessarily produce satisfactory agent behavior. Consequently, adjustable autonomy has become the hallmark of autonomous systems development that influences an agent to exhibit satisfactory behavior. To perform such influences, however, a dynamic adjustment mechanism is needed to be configured. The influences are costly in time and implementation especially for systems with time-critical domain. They might negatively influence agent decisions and cause system disturbance. In this paper, we propose a framework to govern an agent autonomy adjustment and minimize system disturbance. The main components of the proposed framework are the Planner, Scheduler and Controller (PSC) that conform to the current trends in automated systems. Two modules are also suggested which are Autonomy Analysis Module (AAM) and Situation Awareness Module (SAM). They are accordingly used to distribute the autonomy and provide balance to the system so that it's local and global desires do not conflict. � 2013 Springer-Verlag.