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A dominant paradigm in visual intelligence treats semantics as a static property of latent representations, assuming that meaning can be discovered through geometric proximity in high dimensional embedding spaces. In this work, we argue…

Artificial Intelligence · Computer Science 2026-02-24 Xiu Li

Word representations induced from models with discrete latent variables (e.g.\ HMMs) have been shown to be beneficial in many NLP applications. In this work, we exploit labeled syntactic dependency trees and formalize the induction problem…

Computation and Language · Computer Science 2016-02-08 Simon Šuster , Gertjan van Noord , Ivan Titov

Based on a functional-integral formalism, a generalization of the self-energy-functional theory (SFT) is proposed which is applicable to systems of interacting electrons with disorder. Similar to the pure case without disorder, a…

Strongly Correlated Electrons · Physics 2013-05-29 Michael Potthoff , Matthias Balzer

This paper introduces Energentic Intelligence, a class of autonomous systems defined not by task performance, but by their capacity to sustain themselves through internal energy regulation. Departing from conventional reward-driven…

Artificial Intelligence · Computer Science 2025-06-06 Atahan Karagoz

We formulate the computational processes of perception in the framework of the principle of least action by postulating the theoretical action as a time integral of the free energy in the brain sciences. The free energy principle is…

Neurons and Cognition · Quantitative Biology 2019-02-21 Chang Sub Kim

This paper provides a concise description of the free energy principle, starting from a formulation of random dynamical systems in terms of a Langevin equation and ending with a Bayesian mechanics that can be read as a physics of sentience.…

This paper studies a regression model with functional dependent and explanatory variables, both of which exhibit nonstationary dynamics. The model assumes that the nonstationary stochastic trends of the dependent variable are explained by…

Methodology · Statistics 2025-10-02 Kyungsik Nam , Won-Ki Seo

Formalizing creativity-related concepts has been a long-term goal of Computational Creativity. To the same end, we explore Formal Learning Theory in the context of creativity. We provide an introduction to the main concepts of this…

Artificial Intelligence · Computer Science 2024-05-06 Luís Espírito Santo , Geraint Wiggins , Amílcar Cardoso

This paper proposes a structural and dynamical framework for modeling cognitive processes within a cybernetic perspective. Cognitive states are represented as elements of a state space evolving through an iterative update rule of the form…

Artificial Intelligence · Computer Science 2026-05-26 Carlo Cattani , Dioneia Motta Monte-Serrat

What role does phenotypic complexity play in the systems-level function of an embodied agent? The organismal phenotype is a topologically complex structure that interacts with a genotype, developmental physics, and an informational…

Neurons and Cognition · Quantitative Biology 2022-08-15 Bradly Alicea , Jesse Parent

Active inference is a first principles approach for understanding the brain in particular, and sentient agents in general, with the single imperative of minimizing free energy. As such, it provides a computational account for modelling…

Computer Vision and Pattern Recognition · Computer Science 2022-09-20 Stefano Ferraro , Toon Van de Maele , Pietro Mazzaglia , Tim Verbelen , Bart Dhoedt

Despite its centrality in the philosophy of cognitive science, there has been little prior philosophical work engaging with the notion of representation in contemporary NLP practice. This paper attempts to fill that lacuna: drawing on ideas…

Computation and Language · Computer Science 2023-11-21 Jacqueline Harding

Inferential relations govern our concept use. In order to understand a concept it has to be located in a space of implications. There are different kinds of conditions for statements, i.e. that the conditions represent different kinds of…

Artificial Intelligence · Computer Science 2020-07-07 Florian Richter

It is here proposed an analysis of symbolic and sub-symbolic models for studying cognitive processes, centered on emergence and logical openness notions.The Theory of Logical Openness connects the Physics of system/environment relationships…

Adaptation and Self-Organizing Systems · Physics 2007-05-23 Ignazio Licata

The study of opinions $-$ e.g., their formation and change, and their effects on our society $-$ by means of theoretical and numerical models has been one of the main goals of sociophysics until now, but it is one of the defining topics…

Physics and Society · Physics 2015-09-03 Francesca Giardini , Daniele Vilone , Rosaria Conte

This paper makes a first step towards a logic of learning from experiments. For this, we investigate formal frameworks for modeling the interaction of causal and (qualitative) epistemic reasoning. Crucial for our approach is the idea that…

Artificial Intelligence · Computer Science 2021-12-02 Fausto Barbero , Katrin Schulz , Fernando R. Velázquez-Quesada , Kaibo Xie

In simulating charged systems, it is often useful to treat some ionic components of the system at the mean-field level and solve the Poisson-Boltzmann (PB) equation to get their respective density profiles. The numerically intensive task of…

Soft Condensed Matter · Physics 2013-09-30 Vikram Jadhao , Francisco J. Solis , Monica Olvera de la Cruz

The free energy principle (FEP), as an encompassing framework and a unified brain theory, has been widely applied to account for various problems in fields such as cognitive science, neuroscience, social interaction, and hermeneutics. As a…

Neural and Evolutionary Computing · Computer Science 2023-06-13 Jingwei Liu

Phenomenology is the rigorous descriptive study of conscious experience. Recent attempts to formalize Husserlian phenomenology provide us with a mathematical model of perception as a function of prior knowledge and expectation. In this…

Neurons and Cognition · Quantitative Biology 2022-10-31 Mahault Albarracin , Riddhi J. Pitliya , Maxwell J. D. Ramstead , Jeffrey Yoshimi

Quantitative modeling of human brain activity based on language representations has been actively studied in systems neuroscience. However, previous studies examined word-level representation, and little is known about whether we could…

Computer Vision and Pattern Recognition · Computer Science 2018-02-08 Eri Matsuo , Ichiro Kobayashi , Shinji Nishimoto , Satoshi Nishida , Hideki Asoh