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Measuring autonomy by multivariate autoregressive modelling
I introduce a quantitative measure of autonomy based on a time series analysis adapted from 'Granger causality'. A system is considered autonomous if prediction of its future evolution is enhanced by considering its own past states, as compared to predictions based on past states of a set of external variables. The proposed measure, Gautonomy, amplifies the notion of autonomy as 'self-determination'. I illustrate G-autonomy by application to example time series data and to an agent-based model of predator-prey behaviour. Analysis of the predator-prey model shows that evolutionary adaptation can enhance G-autonomy.
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Publication status
- Published
ISSN
0302-9743Publisher URL
Volume
4648Pages
10Presentation Type
- paper
Event name
9th European Conference on Artificial LifeEvent location
Lisbon, PortugalEvent type
conferenceISBN
978-3-540-74912-7Department affiliated with
- Informatics Publications
Full text available
- No
Peer reviewed?
- Yes
Editors
LM Rocha, A Coutinho, FAE Costa, Inman Harvey, E CostaLegacy Posted Date
2012-02-06Usage metrics
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