File(s) not publicly available
Measuring emergence via nonlinear Granger causality
The concept of emergence is central to artificial life and complexity science, yet quantitative, intuitive, and easy-to-apply measures of emergence are surprisingly lacking. Here, I introduce a just such a measure, G-emergence, which operationalizes the notion that an emergent process is both dependent upon and autonomous from its underlying causal factors. G-emergence is based on a nonlinear time series analysis adapted from ‘Granger causality’ and it provides a measure not only of emergence but also of apparent ‘downward causation’. I illustrate the measure by application to a canonical example of emergence, an agent-based simulation of bird flocking, and I discuss its potential impact on perhaps the most challenging of all scientific problems involving emergence: consciousness.
History
Publication status
- Published
Publisher
MIT PressPages
10Presentation Type
- paper
Event name
Artificial Life XI: Proceedings of the Eleventh International Conference on the Simulation and Synthesis of Living SystemsEvent type
conferenceISBN
9780260000000Department affiliated with
- Informatics Publications
Full text available
- No
Peer reviewed?
- Yes
Editors
S Bullock, M Bedau, R Watson, J NobleLegacy Posted Date
2012-02-06Usage metrics
Categories
No categories selectedKeywords
Licence
Exports
RefWorks
BibTeX
Ref. manager
Endnote
DataCite
NLM
DC