On the cross-disciplinary nature of guided self-organisation

Mikhail Prokopenko*, Daniel Polani, Nihat Ay

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingForeword/postscript/introductionpeer-review


Self-organisation is pervasive: neuronal ensembles self-organise into complex spatio-temporal spike patterns which facilitate synaptic plasticity and long-term consolidation of information; large-scale natural or social systems, as diverse as forest fires, landslides, or epidemics, produce spontaneous scale-invariant behaviour; robotic modules self-organise into coordinated motion patterns; individuals within a swarm achieve collective coherence out of isolated actions; and so on. Selforganisation is also valuable: the resultant increase in an internal organisation brings benefits to the (collective) organism, be it a learning brain, a co-evolving ecosystem, an adapting modular robot, or a re-configuring swarm. These benefits are typically realised in increased resilience to external disturbances, adaptivity to novel tasks, and scalability with respect to new challenges. However, self-organisation is difficult to engineer on demand: the intricate fabric of interactions within a self-organising system cannot follow a simple-minded blueprint and resists crude interventions.
Original languageEnglish
Title of host publicationGuided self-organization
Subtitle of host publicationinception
EditorsMikhail Prokopenko
Place of PublicationBerlin; Heidelberg
PublisherSpringer, Springer Nature
Number of pages13
ISBN (Print)9783642537332
Publication statusPublished - 2014

Publication series

NameEmergence Complexity and Computation
ISSN (Print)2194-7287

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