Measuring autonomy and emergence via Granger causality

Seth, Anil K (2010) Measuring autonomy and emergence via Granger causality. Artificial Life, 16 (2). pp. 179-196. ISSN 10645462

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Abstract

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 the 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.

Item Type: Article
Schools and Departments: School of Engineering and Informatics > Informatics
Depositing User: Anil Seth
Date Deposited: 06 Feb 2012 21:09
Last Modified: 14 Mar 2017 00:26
URI: http://sro.sussex.ac.uk/id/eprint/29803

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