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.
|Title of host publication||Unknown Host Publication|
|Number of pages||5|
|Publication status||Published (in print/issue) - 2009|
|Event||the International Conference on Machine Learning and Cybernetics (ICMLC) 2009 - |
Duration: 1 Jan 2009 → …
|Conference||the International Conference on Machine Learning and Cybernetics (ICMLC) 2009|
|Period||1/01/09 → …|