activity
20062026
most citedLow Algorithmic Complexity Entropy-deceiving Graphs

85 citations · 742 across the 80 of their papers we have counts for

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Showing 2017Show all

8 papers · 1 filter

cs.ET2017★ 1 cited

Slime mould: the fundamental mechanisms of cognition

Jordi Vallverdu, Oscar Castro, Richard Mayne +7

The slime mould Physarum polycephalum has been used in developing unconventional computing devices for in which the slime mould played a role of a sensing, actuating, and computing…

cs.IT2017

Coding-theorem Like Behaviour and Emergence of the Universal Distribution from Resource-bounded Algorithmic Probability

Hector Zenil, Liliana Badillo, Santiago Hernández-Orozco +1

Previously referred to as `miraculous' in the scientific literature because of its powerful properties and its wide application as optimal solution to the problem of induction/infe…

q-bio.OT2017

An Algorithmic Information Calculus for Causal Discovery and Reprogramming Systems

Hector Zenil, Narsis A. Kiani, Francesco Marabita +5

We demonstrate that the algorithmic information content of a system is deeply connected to its potential dynamics, thus affording an avenue for moving systems in the information-th…

cs.NE2017★ 1 cited

Algorithmically probable mutations reproduce aspects of evolution such as convergence rate, genetic memory, and modularity

Santiago Hernández-Orozco, Narsis A. Kiani, Hector Zenil

Natural selection explains how life has evolved over millions of years from more primitive forms. The speed at which this happens, however, has sometimes defied formal explanations…

q-bio.QM2017

Training-free Measures Based on Algorithmic Probability Identify High Nucleosome Occupancy in DNA Sequences

Hector Zenil, Peter Minary

We introduce and study a set of training-free methods of information-theoretic and algorithmic complexity nature applied to DNA sequences to identify their potential capabilities t…

q-bio.MN2017

HiDi: An efficient reverse engineering schema for large scale dynamic regulatory network reconstruction using adaptive differentiation

Yue Deng, Hector Zenil, Jesper Tégner +1

The use of differential equations (ODE) is one of the most promising approaches to network inference. The success of ODE-based approaches has, however, been limited, due to the dif…