Measuring Autonomy and Emergence via Granger Causality
Artificial Life January 12, 2010 Anil K. Seth 85 citations
Quantitative measures for autonomy and emergence, grounded in Granger causality and multivariate autoregression, are introduced and validated. G-autonomy quantifies how much a variable's past predicts its own future beyond external factors, while G-emergence measures a process's simultaneous dependence on and autonomy from its underlying causes. Applied to agent-based models, evolutionary adaptation increases autonomy in a predation model, and a flocking model demonstrates both emergence and downward causation. The work connects these measures to broader discussions of autonomy, emergence, and consciousness.