Algorithmic information theory
Algorithmic information theory
Theories of computational complexity
Theories of computational complexity
On the Length of Programs for Computing Finite Binary Sequences
Journal of the ACM (JACM)
A Machine-Independent Theory of the Complexity of Recursive Functions
Journal of the ACM (JACM)
On the Length of Programs for Computing Finite Binary Sequences: statistical considerations
Journal of the ACM (JACM)
A Theory of Program Size Formally Identical to Information Theory
Journal of the ACM (JACM)
Information and Randomness: An Algorithmic Perspective
Information and Randomness: An Algorithmic Perspective
Elements of the Theory of Computation
Elements of the Theory of Computation
On minimal-program complexity measures
STOC '69 Proceedings of the first annual ACM symposium on Theory of computing
Algorithmic complexity of recursive and inductive algorithms
Theoretical Computer Science - Super-recursive algorithms and hypercomputation
Algorithmic complexity as a criterion of unsolvability
Theoretical Computer Science
Process complexity and effective random tests
Journal of Computer and System Sciences
A note on blum static complexity measures
WTCS'12 Proceedings of the 2012 international conference on Theoretical Computer Science: computation, physics and beyond
Complexity-based induction systems: Comparisons and convergence theorems
IEEE Transactions on Information Theory
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In this paper we prove that plain complexity induces the weakest form of randomness for all Blum Universal Static Complexity Spaces [11]. As a consequence, there is all infinite sequences have an infinite number of non-random prefixes with respect to any given Blum Universal Static Complexity Space. This is a generalization of the result obtained by Solovay [27] and Calude [7] for plain complexity, and also of the result obtained by Câmpeanu [10], and independently, later on, by Bienvenu and Downey in [1] for prefix-free complexity.