Measuring autonomy by multivariate autoregressive modelling

Seth, Anil (2007) Measuring autonomy by multivariate autoregressive modelling. In: 9th European Conference on Artificial Life, Lisbon, Portugal.

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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.

Item Type: Conference or Workshop Item (Paper)
Schools and Departments: School of Engineering and Informatics > Informatics
Depositing User: Anil Seth
Date Deposited: 06 Feb 2012 20:11
Last Modified: 07 Jun 2012 15:30
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