14 papers · ranked by Valyu relevance
Charles Alexandre Bédard, Geoffroy Bergeron, Paul M. B. Vitányi
We suggest a quantitative and objective notion of emergence. Our proposal uses algorithmic information theory as a basis for an objective framework in which a bit string encodes observational data. A plurality of drops in the Kolmogorov structure function of such a string is seen as the hallmark of emergence. Our…
Zoe Leyva-Acosta, Eduardo Acuña Yeomans, Francisco Hernández-Quiroz, Ming Li
Algorithmic complexity is a foundational notion in theoretical computer science, but its incomputability has led to two families of practical estimators: compression-based and program-execution-based (e.g., the Coding Theorem Method, CTM). Despite widespread use, the correspondence between these paradigms remains…
Hector Zenil, James A. R. Marshall, Jesper Tegnér
Being able to objectively characterize the intrinsic complexity of behavioral patterns resulting from human or animal decisions is fundamental for deconvolving cognition and designing autonomous artificial intelligence systems. Yet complexity is difficult in practice, particularly when strings are short. By numerically…
Zoe Leyva-Acosta, Eduardo Acuña Yeomans, Francisco Hernandez-Quiroz, Boris Ryabko
'Boris Ryabko'] We study practical approximations of Kolmogorov prefix complexity (K) using IMP2, a high-level programming language. Our focus is on investigating the optimality of the interpreter for this language as the reference machine for the Coding Theorem Method (CTM). This method is designed to address…
Thomas Chambon, Jean-Loup Guillaume, Jeanne Lallement, Éloi Bossé
Predicting how an individual will perceive the visual complexity of a piece of information is still a relatively unexplored domain, although it can be useful in many contexts such as for the design of human-computer interfaces. We propose here a new method, called Information Complexity Ranking (ICR) to rank objects…
Daniel Algom, Daniel Fitousi, Andrei Khrennikov
In 1948, Claude Shannon published a revolutionary paper on communication and information in engineering, one that made its way into the psychology of perception and changed it for good. However, the path to truly successful applications to psychology has been slow and bumpy. In this article, we present a readable…
Daniel G. Brown, Tiasa Mondol, Colin Johnson, Juan Romero + 1 more
We discuss how to assess computationally the aesthetic value of “small” objects, namely those that have short digital descriptions. Such small objects still matter: they include headlines, poems, song lyrics, short musical scripts and other culturally crucial items. Yet, small objects are a confounding case for our…
Eduardo Y. Sakabe, Felipe S. Abrahão, Alexandre Simões, Esther Colombini + 3 more
Understanding and controlling the complexity of neural networks is a central challenge in machine learning, with implications for generalization, optimization, and model capacity. While most approaches rely on entropy-based loss functions and statistical metrics, these measures often fail to capture deeper, causally…
Christopher P. Kempes, Michael Lachmann, Andrew Iannaccone, G. Matthew Fricke + 3 more
'G. Matthew Fricke' 'M. Redwan Chowdhury' 'Sara I. Walker' 'Leroy Cronin'] Assembly theory (AT) quantifies selection using the assembly equation, identifying complex objects through the assembly index, the minimal steps required to build an object from basic parts, and copy number, the observed instances of the object.…
Felipe S. Abrahão, Hector Zenil
One of the challenges of defining emergence is that one observer’s prior knowledge may cause a phenomenon to present itself as emergent that to another observer appears reducible. By formalizing the act of observing as mutual perturbations between dynamical systems, we demonstrate that the emergence of algorithmic…
Amirmohammad Farzaneh, Justin P. Coon, Mihai-Alin Badiu, Narsis A. Kiani + 2 more
'Narsis A. Kiani' 'Hector Zenil' 'Jesper Tegnér'] Throughout the years, measuring the complexity of networks and graphs has been of great interest to scientists. The Kolmogorov complexity is known as one of the most important tools to measure the complexity of an object. We formalized a method to calculate an upper…
Tiasa Mondol, Daniel G. Brown, Ercan Kuruoglu
We build an analysis based on the Algorithmic Information Theory of computational creativity and extend it to revisit computational aesthetics, thereby, improving on the existing efforts of its formulation. We discuss Kolmogorov complexity, models and randomness deficiency (which is a measure of how much a model falls…
Juan Pablo Franco, Karlo Doroc, Nitin Yadav, Peter Bossaerts + 1 more
'Carsten Murawski'] The survival of human organisms depends on our ability to solve complex tasks in the face of limited cognitive resources. However, little is known about the factors that drive the complexity of those tasks. Here, building on insights from computational complexity theory, we quantify the…
Edward A. Lee
“Rationality” in Simon's “bounded rationality” is the principle that humans make decisions on the basis of step-by-step (algorithmic) reasoning using systematic rules of logic to maximize utility. “Bounded rationality” is the observation that the ability of a human brain to handle algorithmic complexity and large…