Emergence Versus Self-Organisation: Different Concepts but Promising When Combined

By Tom De Wolf, Tom Holvoet. Engineering Self-Organising Systems, 2004

423 citations recorded by the source corpus.

Subfields: Cognitive Neuroscience, Mechanical Engineering, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/93d7e5360197f0024e55f809586efde8ce8e8434

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Cognitive Neuroscience

1. Z. Dörnyei

In Mechanical Engineering

1. Z. Dörnyei

In Statistical and Nonlinear Physics

1. Fabio Boschetti
2. Mikhail Prokopenko
3. Alex J. Ryan
4. Z. Dörnyei

Citations in the corpus

• Researching complex dynamic systems: ‘Retrodictive qualitative modelling’ in the language classroom (2011, background): “This restricted range is due to the system’s self-organisational capacity – it is, in fact, the very essence of system selforganisation; as De Wolf & Holvoet (2005) explain, self-organisation proper always leads to an increase in the order of the system behaviour.”
• An information-theoretic primer on complexity, self-organization, and emergence (2009, background): “For example, De Wolf and Holvoet [24] refer to complexity as a measure of redundancy or structure in the system.”
• A survey on engineering approaches for self-adaptive systems (2015, methodology): “For MASs it is claimed, that ”they are especially suited to develop software systems that are decentralized, can deal flexibly with dynamic conditions, and are open to system components that come and go” [79].”