The calculi of emergence: computation, dynamics and induction
Proceedings of the NATO advanced research workshop and EGS topical workshop on Chaotic advection, tracer dynamics and turbulent dispersion
Automata, Languages, and Machines
Automata, Languages, and Machines
Artificial Life
Cycle structure in automata and the holonomy decomposition
Acta Cybernetica
CIAA'04 Proceedings of the 9th international conference on Implementation and Application of Automata
Distributed online evolution: an algebraic problem?
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Algebraic analysis of the computation in the belousov-zhabotinksy reaction
IPCAT'12 Proceedings of the 9th international conference on Information Processing in Cells and Tissues
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Beyond complexity measures, sometimes it is worthwhile in addition to investigate how complexity changes structurally, especially in artificial systems where we have complete knowledge about the evolutionary process. Hierarchical decomposition is a useful way of assessing structural complexity changes of organisms modeled as automata, and we show how recently developed computational tools can be used for this purpose, by computing holonomy decompositions and holonomy complexity. To gain insight into the evolution of complexity, we investigate the smoothness of the landscape structure of complexity under minimal transitions. As a proof of concept, we illustrate how the hierarchical complexity analysis reveals symmetries and irreversible structure in biological networks by applying the methods to the lac operon mechanism in the genetic regulatory network of Escherichia coli.