Some established and also novel techniques in the field of applications of algorithmic
(Kolmogorov) complexity currently co-exist for the first time and are here reviewed, ranging …

Drawing on various notions from theoretical computer science, we present a novel
numerical approach, motivated by the notion of algorithmic probability, to the problem of …

We investigate the properties of a Block Decomposition Method (BDM), which extends the
power of a Coding Theorem Method (CTM) that approximates local estimations of …

We describe an alternative method (to compression) that combines several theoretical and
experimental results to numerically approximate the algorithmic Kolmogorov–Chaitin …

A method for studying the qualitative dynamical properties of abstract computing machines
based on the approximation of their program-size complexity using a general lossless …

Unconventional computing is about breaking boundaries in thinking, acting and computing.
Typical topics of this non-typical field include, but are not limited to physics of computation …

We introduce and develop a method that demonstrates that the algorithmic information
content of a system can be used as a steering handle in the dynamical phase space, thus …

We propose a measure based upon the fundamental theoretical concept in algorithmic
information theory that provides a natural approach to the problem of evaluating n …

Algorithmic entropy can be viewed as a special case of the entropy studied in statistical
mechanics. This viewpoint allows us to apply many techniques developed for use in …

Inferring algorithmic structure in data is essential for discovering causal generative models.
In this research, we present a quantum computing framework using the circuit model, for …