Al-Rifaie, Mohammad Majid ORCID: https://orcid.org/0000-0002-1798-9615 and Bishop, Mark (2013) Swarm intelligence and weak artificial creativity. In: Creativity and (Early) Cognitive Development: A perspective from Artificial Creativity, Developmental AI and Robotics. AAAI Spring Symposium Series 2013 AAAI Spring Symposium Series . Association for the Advancement of Artificial Intelligence (AAAI) Press, Palo Alto, California, pp. 14-19. ISBN 978-1577355991

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Abstract

Swarm intelligence via its infamous struggle to identify a suitable balance between exploration and exploitation phases, provides a valuable mean to approach artificial creativity. This work deploys two swarm intelligence algorithms, one simulating the behaviour of birds flocking and fish schooling (Particle Swarm Optimisation) and the other mimicking the behaviour of ants foraging (Stochastic Diffusion Search) in order to lay the foundation for a discussion addressing the concepts of freedom and constraint within the topic of creativity in general, and more specifically their impact on the artificial creativity of the underlying systems. An analogy is drawn on mapping these two ‘prerequisites’ of creativity onto the two well-known aforementioned phases of exploration and exploitation in swarm intelligence algorithms. This is accompanied by the visualisation of the behaviour of the swarms whose performance are evaluated in the context of the arguments presented. Additionally in the spirit of Searle’s definition of weak and strong artificial intelligence, a discussion on weak vs. strong artificial creativity in swarm intelligence systems is presented.

Item Type:	Conference Proceedings
Title of Proceedings:	Creativity and (Early) Cognitive Development: A perspective from Artificial Creativity, Developmental AI and Robotics
Uncontrolled Keywords:	Weak artificial creativity, swarm intelligence
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Faculty / School / Research Centre / Research Group:	Faculty of Liberal Arts & Sciences > Computational Science & Engineering Group (CSEH) Faculty of Engineering & Science > School of Computing & Mathematical Sciences (CMS) Faculty of Engineering & Science
Related URLs:	Publisher
Last Modified:	04 Mar 2022 13:08
URI:	http://gala.gre.ac.uk/id/eprint/21025

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