Paper Info
Title
Defining Tasks and Actions Complexity-Levels via Their Deliberation Intensity Measures in the Layered Adjustable Autonomy Model
Abstract
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.
Year
DOI
Venue
2014
10.1109/IE.2014.15
Intelligent Environments
Keywords
Field
DocType
autonomous agent, multi-agent system , layered adjustable autonomy , dynamic environment, deliberation measures, complexity-level, decision-making
Deliberation,Autonomous agent,Computer science,Autonomy,Multi-agent system,Human–computer interaction
Conference
Citations 
PageRank 
References 
7
0.51
5
Authors
6
Name
Order
Citations
PageRank
Salama A. Mostafa116621.72
Saraswathy Shamini Gunasekaran2304.09
Mohd Sharifuddin Ahmad318934.38
Azhana Ahmad46612.93
Muthukkaruppan Annamalai5415.67
Aida Mustapha69026.18