Swarm intelligence: from natural to artificial systems
Swarm intelligence: from natural to artificial systems
Programming with stigmergy: using swarms for construction
ICAL 2003 Proceedings of the eighth international conference on Artificial life
Utilizing Stigmergy in Support of Autonomic Principles
SKG '07 Proceedings of the Third International Conference on Semantics, Knowledge and Grid
Cognitive stigmergy: towards a framework based on agents and artifacts
E4MAS'06 Proceedings of the 3rd international conference on Environments for multi-agent systems III
Trace signals: the meanings of stigmergy
E4MAS'06 Proceedings of the 3rd international conference on Environments for multi-agent systems III
E4MAS'04 Proceedings of the First international conference on Environments for Multi-Agent Systems
A survey of environments and mechanisms for human-human stigmergy
E4MAS'05 Proceedings of the 2nd international conference on Environments for Multi-Agent Systems
Stigmergy in web 2.0: a model for site dynamics
Proceedings of the 3rd Annual ACM Web Science Conference
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Stigmergy is a biological term used when discussing insect or swarm behaviour, and describes a model supporting environmental communication separately from artefacts or agents. This phenomenon is demonstrated in the behavior of ants and their food gathering process when following pheromone trails, or similarly termites and their termite mound building process. What is interesting with this mechanism is that highly organized societies are achieved without an apparent management structure. Stigmergic behavior is implicit in the Web where the volume of users provides a self-organizing and self-contextualization of content in sites which facilitate collaboration. However, the majority of content is generated by a minority of the Web participants. A significant contribution from this research would be to create a model of Web stigmergy, identifying virtual pheromones and their importance in the collaborative process. This paper explores how exploiting stigmergy has the potential of providing a valuable mechanism for identifying and analyzing online user behavior recording actionable knowledge otherwise lost in the existing web interaction dynamics. Ultimately this might assist our building better collaborative Web sites.