Measuring autonomy by multivariate autoregressive modelling

Abstract

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-prev model shows that evolutionary adaptation can enhance © Springer-Verlag Berlin Heidelberg 2007.