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At its core is what he calls the Principle of Computational Equivalence, which is that all systems that exhibit more than simple behavior (like the automata cells on this page) have equal computational powers -- they are all universal computers.
He also seems to want to take credit for complexity theory itself.There's no short cutOne last act of daring is Mr Wolfram's principle of computational equivalence, by which he lumps together all complex phenomena as equally complex manifestations of the same underlying rules for cellular automata.
Even granting the truth of the two premises (that is, even granting the troublesome Principle of Computational Equivalence), it is doubtful the desired conclusion would follow.
The principle of computational analysis has been described elsewhere [ 10, 11].
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In particular, we will focus on how adaptation services can be used to improve dependability in instrumented cyber-physical systems based on the principles of "computational reflection".
For the reader to gain appreciation for the complexity of these calculations and to promote responsible usage of available computational software, basic principles of computational theory are presented along with simple guidelines for the nonexpert user.
Specifically, we discuss essential principles of computational methods that are required to meet the key challenges of the RNA-seq data analyses, development of various bioinformatics tools, challenges associated with the RNA-seq applications, and examples that represent the advances made so far in the characterization of the transcriptome.
The rules for time evolution can be thought of as a search algorithm, whose details should be constrained by a stronger principle of "minimal computational complexity".
We argue for a principle of "limited computational complexity" governing early universe dynamics as simulated by this supercomputer, which translates to a global measure for regulating the infinities of eternal inflation.
In turn the principle of functional (computational) segregation - as reflected in the typology of unimodal motor and sensory or heteromodal association areas of the cortex - is known to be mirrored both in the macroscopic white matter network topology [10] and in functional connectivity networks [11].
To find the optimal feature subset from the feature space with N features, all the combinations of N features should be tried from the point of view of the exhaustion principle, which is of computational intractability.
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