Linked Data as Stigmergic Medium for Decentralized Coordination

Torsten Spieldenner, Melvin Chelli

In: Proceedings of the 16th International Conference on Software Technologies. International Conference on Software Technologies (ICSOFT-2021) July 6-8 Virtual Pages 347-357 ISBN 978-989-758-523-4 SCITEPRESS 2021.


Algorithms inspired by nature have gained focus in research as a solution to classic coordination and optimization problems. A certain type of these algorithms employs principles of stigmergy: in stigmergic systems, coordination arises from agents leaving traces of their actions in the environment, or medium, that they work on. Other agents instinctively adapt their behavior based on the traces, by which, in the end, the fulfillment of a higher goal emerges from elementary actions of many, rather than thorough planning of complex actions of a few. Despite the perceivable uptake of stigmergic algorithms for coordination in various domains, a common clear understanding of a suitable digital stigmergic medium is lacking. It should however be assumed that a well-defined, properly modelled, and technically sound digital medium provides a crucial basis for correct, efficient and transferable stigmergic algorithms. In this paper, we motivate read-write Linked Data as generic medium for decentralized stigmergic coordination algorithms. We show how Linked Data fulfills a set of core requirements that we derived for stigmergic media from relevant literature, provide an application example from the domain of digital manufacturing, and finally provide a working example algorithm for stigmergic decentralized coordination.


German Research Center for Artificial Intelligence
Deutsches Forschungszentrum für Künstliche Intelligenz