Weeks, Andrew (2010) Neutral Emergence and Coarse Graining Cellular Automata. PhD thesis, University of York.
Available under License Creative Commons Attribution Noncommercial 2.0 UK: England & Wales.
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 Sep 2016 12:21|