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Neutral Emergence and Coarse Graining Cellular Automata

Weeks, Andrew (2010) Neutral Emergence and Coarse Graining Cellular Automata. PhD thesis, University of York.

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Abstract

Emergent systems are often thought of as special, and are often linked to desirable properties like robustness, fault tolerance and adaptability. But, though not well understood, emergence is not a magical, unfathomable property. We introduce neutral emergence as a new way to explore emergent phenomena, showing that being good enough, enough of the time may actually yield more robust solutions more quickly. We then use cellular automata as a substrate to investigate emergence, and find they are capable of exhibiting emergent phenomena through coarse graining. Coarse graining shows us that emergence is a relative concept - while some models may be more useful, there is no correct emergent model - and that emergence is lossy, mapping the high level model to a subset of the low level behaviour. We develop a method of quantifying the 'goodness' of a coarse graining (and the quality of the emergent model) and use this to find emergent models - and, later, the emergent models we want - automatically.

Item Type: Thesis (PhD)
Keywords: cellular automata, ca, emergence, robustness, adaptability, coarse graining
Academic Units: The University of York > Computer Science (York)
Depositing User: Mr Andrew Weeks
Date Deposited: 16 May 2012 08:51
Last Modified: 08 Aug 2013 08:48
URI: http://etheses.whiterose.ac.uk/id/eprint/2256

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