Journal
ARTIFICIAL LIFE
Volume 16, Issue 2, Pages 179-196Publisher
MIT PRESS
DOI: 10.1162/artl.2010.16.2.16204
Keywords
Autonomy; emergence; Granger causality; consciousness; flocking; evolution
Funding
- EPSRC [EP/G007543/1]
- EPSRC [EP/G007543/1] Funding Source: UKRI
- Engineering and Physical Sciences Research Council [EP/G007543/1] Funding Source: researchfish
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Concepts of emergence and autonomy are central to artificial life and related cognitive and behavioral sciences. However, quantitative and easy-to-apply measures of these phenomena are mostly lacking. Here, I describe quantitative and practicable measures for both autonomy and emergence, based on the framework of multivariate autoregression and specifically Granger causality. G-autonomy measures the extent to which knowing the past of a variable helps predict its future, as compared to predictions based on past states of external (environmental) variables. G-emergence measures the extent to which a process is both dependent upon and autonomous from its underlying causal factors. These measures are validated by application to agent-based models of predation (for autonomy) and flocking (for emergence). In the former, evolutionary adaptation enhances autonomy; the latter model illustrates not only emergence but also downward causation. I end with a discussion of relations among autonomy, emergence, and consciousness.
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