J
James P. Crutchfield
Researcher at University of California, Davis
Publications - 338
Citations - 20738
James P. Crutchfield is an academic researcher from University of California, Davis. The author has contributed to research in topics: Entropy rate & Dynamical systems theory. The author has an hindex of 62, co-authored 314 publications receiving 19299 citations. Previous affiliations of James P. Crutchfield include University of California, Santa Cruz & PARC.
Papers
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Journal ArticleDOI
Computing the Topological Entropy of Maps
TL;DR: An algorithm for determining the topological entropy of a unimodal map of the interval given its kneading sequence is given and it is shown that this algorithm converges exponentially in the number of letters of the kneaded sequence.
Journal ArticleDOI
Objects that make objects: the population dynamics of structural complexity
TL;DR: In this paper, the evolutionary emergence of structural complexity in physical processes is analyzed and the evolution to increased organization is dominated by the spontaneous creation of structural hierarchies and this, in turn, is facilitated by the innovation and maintenance of relatively low-complexity but general individuals.
Book ChapterDOI
The Evolutionary Unfolding of Complexity
TL;DR: The architectural view of subbasins and portals in genotype space clarifies how frozen accidents and the resulting phenotypic constraints guide the evolution to higher complexity.
Posted Content
Neutral Evolution of Mutational Robustness
TL;DR: In this article, the authors introduced and analyzed a general model of a population evolving over a network of selectively neutral genotypes and showed that the population's limit distribution on the neutral network is solely determined by the network topology and given by the principal eigenvector of the network's adjacency matrix.
Book ChapterDOI
Observing Complexity and the Complexity of Observation
TL;DR: The distortions introduced by the measurement process can lead to drastic consequences for an observer’s ability to infer structure in its environment.