Defining tasks and actions complexity-levels via their deliberation intensity measures in the layered adjustable autonomy model

• Main Authors: Mostafa, S.A., Gunasekaran, S.S., Ahmad, M.S., Ahmad, A., Annamalai, M., Mustapha, A.
• Format: Conference Paper
• Language: English
• Published: 2017
• Subjects: autonomous agent; complexity-level; decision-making; deliberation measures; dynamic environment; Layered Adjustable Autonomy (LAA); multi-agent system (MAS)

In Multi-agent Systems (MAS), agents perform a variety of actions to autonomously complete a number of tasks. In this paper, we describe a mechanism to measure a task's deliberation intensity and apply the mechanism in the Layered Adjustable Autonomy (LAA) model. Basically, the number of actions that the agents need to do to complete a particular task determines the task's deliberation intensity. Consequently, each of the actions deliberation intensity determines its complexity-level. Actions complexity levels are categorized as high-level if the action is deliberative, intermediate-level if the action pseudo-deliberative and low-level if the action is non-deliberative. Ultimately, the deliberation intensity measure of a task and its actions identify different aspects of the agents' and the actions' parameters including the deliberation length and the autonomy configuration of the LAA model. © 2014 IEEE.