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Rule Discovery from Swarm Systems

Stoops, David, Wang, Hui, Moore, George and Bi, Yaxin (2009) Rule Discovery from Swarm Systems. In: the International Conference on Machine Learning and Cybernetics (ICMLC) 2009. IEEE Press. 5 pp. [Conference contribution]

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Abstract

Rules govern many of the operations carried out within real world systems, both man-made and natural. Man-made systems, such as air traffic control, employ known rules to control its operations. Known rules can be used to predict patterns, or used as a method of control. Natural systems, such insect ecologies, implement unknown rules. Unknown rules could provide much insight into how a system works, or alternatively how to further understand the interactions within a system. Swarm systems are a form of biological grouping within the natural world, these include bee and ants, but can be expanded as far as human groups. Discovery of rules from a swarm could provide a means to understanding the interactions and rules within the group. This would provide great value with respect to providing the rules employed and the roles within the group. This paper presents a framework for this task, with the presentation of the issues surrounding it, and some of the early results gathered from the mining process.

Item Type:Conference contribution (Paper)
Faculties and Schools:Faculty of Computing & Engineering
Faculty of Computing & Engineering > School of Computing and Mathematics
Research Institutes and Groups:Computer Science Research Institute
Computer Science Research Institute > Artificial Intelligence and Applications
ID Code:25635
Deposited By: Dr Yaxin Bi
Deposited On:22 Jan 2015 10:31
Last Modified:22 Jan 2015 10:31

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