A New Approach to Complex Systems Dynamics

From Santa Fe Institute

John Harte, University of California, Berkeley & SFI Whereas information-theoretic top-down inferential methods can often successfully predict static probability distributions over microvariables when state variables are constant in time, such methods generally fail in dynamic systems. Building on the observation that complex systems often exhibit bi-directional cross-scale causation, we combine information-theoretic top-down statistical inference with agent-based (bottom-up) process modeling...