CIaaS - computational intelligence as a service with Athena. (December 2018)

• Record Type: Journal Article
• Authors: Oliveira, Pedro; Santos Neto, Pedro; Britto, Ricardo; Rabêlo, Ricardo; Braga, Ronyerison; Souza, Matheus
• Is Part Of: Computer languages, systems & structures. Volume 54(2018)
• Page Start: 95
• Page End: 118
• Publication Date: 2018-12
• Subjects: Computational intelligence -- Tool -- Visual programming; Programming languages (Electronic computers) -- Periodicals; Computer networks -- Periodicals; Computer architecture -- Periodicals; Computer systems -- Periodicals; Langage de programmation; Réseau d'ordinateurs; Architecture d'ordinateur; Périodique électronique (Descripteur de forme); Ressource Internet (Descripteur de forme); 005.13
• DOI: 10.1016/j.cl.2018.04.003
• Languages: English
• ISSNs: 1477-8424

Abstract

Highlights: A visual cloud-based platform to design and evaluate CI solutions is proposed. Athena uses a new paradigm called CIaaS for ease the development of CI systems. Athena has 35 built-in modules that can be connected to create hybrid systems. The work present and validate through an experiment a more mature version of Athena. Empirical study showed that Athena reduces effort to implements CI-based solutions. Abstract: Computational Intelligence (CI) is a sub-branch of Artificial Intelligence (AI) that focus on studying adaptive mechanisms to enable intelligent behavior in complex environments. CI techniques have been successful in solving complex problems in many different knowledge areas. However, despite their usefulness, developing solutions based on CI techniques is not a trivial activity, since it involves the codification/adaptation of algorithms to specific context and problems. In this paper, we present and validate through a quasi -experiment a new paradigm to develop CI-based solutions using a more mature version of Athena (2.0): Computational Intelligence as a Service (CIaaS). Using this tool, both researchers and practitioners can design and evaluate CI-based solutions by dragging and dropping components in a visual environment, in a cloud-based platform. The results of the quasi -experiment suggest that our approach can help researchers to design and evaluate CI-based systems in a simple, reliable and fast way.