Jim Crutchfield | Computational Mechanics | Dynamics of Learning | Evolving Cellular Automata | Evolutionary Dynamics




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Welcome to the Computational Mechanics Archive at the Complexity Sciences Center at UC Davis. The central question driving the research described here is,

How does nature compute?

Or, more precisely, How is information processing embedded in dynamical behavior?

The label computational mechanics is simply meant to indicate an extension of the approaches typically found in statistical mechanics. That is, we are concerned with more detailed structural aspects of behavior than those captured solely in terms of probability and degrees of randomness. Beyond focusing on measures of disorder, such as temperature and thermodynamic entropy, we ask the following...

How can we detect and quantify structure in natural processes?

The diverse model classes found in computation theory are key tools in being explicit about how natural information processing mechanisms can be represented and analyzed. However, one quickly comes to the conclusion that contemporary notions of computation and of useful information processing, colored as they are by the recent history of digital computer technology, must be extended in order to be useful within empirical science. Why? Because the processes studied by natural scientists involve systems that are continuous, stochastic, spatially extended, or even some combination of these and other characteristics fall strictly outside the purview of discrete computation theory.