Seminar #20: From Causality to Autonomy: A Quantitative Approach
Next’s week Life & Mind seminar will be Wednesday the 23rd of May, at 16:00 (slightly later than usual) in room Pev 2A2. Anil Seth will lead a discussion on:
From Causality to Autonomy: A Quantitative Approach.
I would like to discuss my recent ECAL submission (reviews expected any time now), in which I develop a new measure of autonomy based on an existing measure of causality. The abstract of the paper is given below, and I attach two short papers: (1) the ECAL submission, and (2) a short summary of my previous work in causal modelling of neural systems. In leading the discussion I won’t assume that either paper has been read, but of course it would help, and the most relevant is naturally the ECAL paper.
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, G-autonomy, 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.