16 citations · 52 across the 14 of their papers we have counts for
18 papers
The Future of Fundamental Science Led by Generative Closed-Loop Artificial Intelligence
Hector Zenil, Jesper Tegnér, Felipe S. Abrahão +17
Recent advances in machine learning and AI, including Generative AI and LLMs, are disrupting technological innovation, product development, and society as a whole. AI's contributio…
A simplicity bubble problem and zemblanity in digitally intermediated societies
Felipe S. Abrahão, Ricardo P. Cavassane, Michael Winter +2
In this article, we discuss the ubiquity of Big Data and machine learning in society and propose that it evinces the need of further investigation of their fundamental limitations.…
An Optimal, Universal and Agnostic Decoding Method for Message Reconstruction, Bio and Technosignature Detection
Hector Zenil, Alyssa Adams, Felipe S. Abrahão +1
We present an agnostic signal reconstruction method for zero-knowledge one-way communication channels in which a receiver aims to interpret a message sent by an unknown source abou…
A Simplicity Bubble Problem in Formal-Theoretic Learning Systems
Felipe S. Abrahão, Hector Zenil, Fabio Porto +3
When mining large datasets in order to predict new data, limitations of the principles behind statistical machine learning pose a serious challenge not only to the Big Data deluge,…
Emergence and algorithmic information dynamics of systems and observers
Felipe S. Abrahão, Hector Zenil
Previous work has shown that perturbation analysis in software space can produce candidate computable generative models and uncover possible causal properties from the finite descr…
An Algorithmic Information Distortion in Multidimensional Networks
Felipe S. Abrahão, Klaus Wehmuth, Hector Zenil +1
Network complexity, network information content analysis, and lossless compressibility of graph representations have been played an important role in network analysis and network m…
Emergence of complex data from simple local rules in a network game
Felipe S. Abrahão, Klaus Wehmuth, Artur Ziviani
As one of the main subjects of investigation in data science, network science has been demonstrated a wide range of applications to real-world networks analysis and modeling. For e…
On the existence of hidden machines in computational time hierarchies
Felipe S. Abrahão, Klaus Wehmuth, Artur Ziviani
Challenging the standard notion of totality in computable functions, one has that, given any sufficiently expressive formal axiomatic system, there are total functions that, althou…
Transtemporal edges and crosslayer edges in incompressible high-order networks
Felipe S. Abrahão, Klaus Wehmuth, Artur Ziviani
This work presents some outcomes of a theoretical investigation of incompressible high-order networks defined by a generalized graph representation. We study some of their network…
Learning the undecidable from networked systems
Felipe S. Abrahão, Ítala M. Loffredo D'Ottaviano, Klaus Wehmuth +2
This article presents a theoretical investigation of computation beyond the Turing barrier from emergent behavior in distributed systems. In particular, we present an algorithmic n…
Expected Emergence of Algorithmic Information from a Lower Bound for Stationary Prevalence
Felipe S. Abrahão, Klaus Wehmuth, Artur Ziviani
We study emergent information in populations of randomly generated networked computable systems that follow a Susceptible-Infected-Susceptible contagion (or infection) model of imi…
On sequential structures in incompressible multidimensional networks
Felipe S. Abrahão, Klaus Wehmuth, Hector Zenil +1
In order to deal with multidimensional structure representations of real-world networks, as well as with their worst-case irreducible information content analysis, the demand for n…
Algorithmic information distortions and incompressibility in uniform multidimensional networks
Felipe S. Abrahão, Klaus Wehmuth, Hector Zenil +1
This article presents a theoretical investigation of generalized encoded forms of networks in a uniform multidimensional space. First, we study encoded networks with (finite) arbit…
Emergent Open-Endedness from Contagion of the Fittest
Felipe S. Abrahão, Klaus Wehmuth, Artur Ziviani
In this paper, we study emergent irreducible information in populations of randomly generated computable systems that are networked and follow a "Susceptible-Infected-Susceptible"…
Minimal Algorithmic Information Loss Methods for Dimension Reduction, Feature Selection and Network Sparsification
Hector Zenil, Narsis A. Kiani, Alyssa Adams +5
We present a novel, domain-agnostic, model-independent, unsupervised, and universally applicable Machine Learning approach for dimensionality reduction based on the principles of a…
Algorithmic Networks: central time to trigger expected emergent open-endedness
Felipe S. Abrahão, Klaus Wehmuth, Artur Ziviani
This article investigates emergence and complexity in complex systems that can share information on a network. To this end, we use a theoretical approach from information theory, c…
The "paradox" of computability and a recursive relative version of the Busy Beaver function
Felipe S. Abrahão
In this article, we will show that uncomputability is a relative property not only of oracle Turing machines, but also of subrecursive classes. We will define the concept of a Turi…
Relativizing an incompressible number and an incompressible function through subrecursive extensions of Turing machines
Felipe S. Abrahão
We show in this article that uncomputability is also a relative property of subrecursive classes built on a recursive relative incompressible function, which acts as a higher-order…