Collaborative Air Traffic Decision Support based on Web-Based Intelligent Argumentation
Abstract
Collaborative Decision Making (CDM) is a process of reaching consensus on a potential solution of an issue through the evaluation of the different possible alternatives. The web-based intelligent computational argumentation system allows concerned decision-making agents to post their arguments on different alternatives, assign degree of strengths to their arguments and identify the most favorable alternative using our system over the internet. Agents are a group of people who participate in the argumentation process for the collaborative decision-making process. Our system resolves the conflicts through intelligent argumentation and captures the rationale of the agents from their arguments. The exchange of information among the agents in the form of arguments helps them present their views and opinions and drives the group towards collective intelligence. In this article, we present an approach on how the intelligent argumentation based collaborative decision support system can facilitate the resolution of conflicts in air traffic management. It could enhance the Ground Delay Program (GDP) and help the Air Traffic Control System Command Center (ATCSCC) to take a better decision depending on the argumentation of Air Route Traffic Control Centers (ARTCC) and agents from different airlines. © 2013 Information Processing Society of Japan.
Recommended Citation
R. S. Arvapally et al., "Collaborative Air Traffic Decision Support based on Web-Based Intelligent Argumentation," Journal of Information Processing, vol. 21, no. 3, pp. 495 - 506, Information Processing Society of Japan, Jan 2013.
The definitive version is available at https://doi.org/10.2197/ipsjjip.21.495
Department(s)
Computer Science
Second Department
Civil, Architectural and Environmental Engineering
Keywords and Phrases
ARTCC; ATCSCC; Collaborative decision support; Fuzzy association memory matrix; Fuzzy inference engine; Ground delay program
International Standard Serial Number (ISSN)
1882-6652; 0387-5806
Document Type
Article - Journal
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2024 Information Processing Society of Japan, All rights reserved.
Publication Date
01 Jan 2013