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Related papers: A Possible Role for Entropy in Creative Cognition

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Entropy notions for $\varepsilon$-incremental practical stability and incremental stability of deterministic nonlinear systems under disturbances are introduced. The entropy notions are constructed via a set of points in state space which…

Optimization and Control · Mathematics 2022-09-13 Michelle S. Chong

We seek general principles of the structure of the cellular collective activity associated with conscious awareness. Can we obtain evidence for features of the optimal brain organization that allows for adequate processing of stimuli and…

Neurons and Cognition · Quantitative Biology 2017-12-27 D. M. Mateos , R. Wennberg , R. Guevara , J. L. Perez Velazquez

This letter seeks to illuminate the profound connection between complexity, self-organization, emergent behaviour, pattern formation, and entropy concepts that are foundational to understanding our universe. By examining these ideas through…

Adaptation and Self-Organizing Systems · Physics 2025-03-25 Vinesh Vijayan , Karpagavalli K , Sandhiya Jenifer J , Prakash R

The rapid evolution of artificial intelligence has led to expectations of transformative impact on science, yet current systems remain fundamentally limited in enabling genuine scientific discovery. This perspective contends that progress…

Artificial Intelligence · Computer Science 2025-12-16 Karthik Duraisamy

As one of the most widespread social dynamics, cooperative behavior is among the most fascinating collective phenomena. Several animal species, from social insects to human beings, feature social groups altruistically working for a common…

This work demonstrates how the concept of the entropic potential of events -- a parameter quantifying the influence of discrete events on the expected future entropy of a system -- can enhance uncertainty quantification, decision-making,…

Artificial Intelligence · Computer Science 2025-08-15 Mark Zilberman

The use of maximum entropy inference in reasoning with uncertain information is commonly justified by an information-theoretic argument. This paper discusses a possible objection to this information-theoretic justification and shows how it…

Artificial Intelligence · Computer Science 2013-04-15 Daniel Hunter

Cognition is not passive data accumulation but the active resolution of uncertainty through symmetry breaking. This paper argues that both cognitive evolution and development unfold via sequential symmetry-breaking transitions that disrupt…

Neurons and Cognition · Quantitative Biology 2025-06-13 Xin Li

Given entropy's central role in multiple areas of physics and science, one important task is to develop a systematic and unifying approach to defining entropy. Games of chance become a natural candidate for characterising the uncertainty of…

Quantum Physics · Physics 2022-02-23 Sarah Brandsen , Isabelle Jianing Geng , Gilad Gour

The principle of entropy increase is not only the basis of statistical mechanics, but also closely related to the irreversibility of time, the origin of life, chaos and turbulence. In this paper, we first discuss the dynamic system…

Statistical Mechanics · Physics 2022-10-11 Zou Dan Dan

Artificial intelligence models and methods commonly lack causal interpretability. Despite the advancements in interpretable machine learning (IML) methods, they frequently assign importance to features which lack causal influence on the…

Machine Learning · Computer Science 2024-01-29 Francisco Nunes Ferreira Quialheiro Simoes , Mehdi Dastani , Thijs van Ommen

To infer information flow in any network of agents, it is important first and foremost to establish causal temporal relations between the nodes. Practical and automated methods that can infer causality are difficult to find, and the subject…

Neural and Evolutionary Computing · Computer Science 2024-12-11 Ali Tehrani-Saleh , Christoph Adami

Humans are adept at uncovering abstract associations in the world around them, yet the underlying mechanisms remain poorly understood. Intuitively, learning the higher-order structure of statistical relationships should involve complex…

Neurons and Cognition · Quantitative Biology 2020-03-26 Christopher W. Lynn , Ari E. Kahn , Nathaniel Nyema , Danielle S. Bassett

This paper introduces a unifying framework that links the Context-Content Uncertainty Principle (CCUP) with optimal transport (OT) via primal-dual inference. We propose that cognitive representations are not static encodings but active dual…

Neurons and Cognition · Quantitative Biology 2025-06-19 Xin Li

Recently it has been demonstrated that causal entropic forces can lead to the emergence of complex phenomena associated with human cognitive niche such as tool use and social cooperation. Here I show that even more fundamental traits…

Information Theory · Computer Science 2016-04-20 Fouad Khan

Over the past two decades, numerous studies have demonstrated how less predictable (i.e., higher surprisal) words take more time to read. In general, these studies have implicitly assumed the reading process is purely responsive: Readers…

Computation and Language · Computer Science 2023-07-17 Tiago Pimentel , Clara Meister , Ethan G. Wilcox , Roger Levy , Ryan Cotterell

Creativity is perhaps what most differentiates humans from other species. It involves the capacity to shift between divergent and convergent modes of thought in response to task demands. Divergent thought has been characterized as the kind…

Neurons and Cognition · Quantitative Biology 2019-12-03 Liane Gabora

Entropy production is often interpreted as a proxy for microscopic disorder or environmental roughness in stochastic systems. We test this interpretation using controlled simulations of overdamped stochastic dynamics on curved surfaces in…

Statistical Mechanics · Physics 2026-02-23 Patrick Romanescu

There is growing interest in studying the languages that emerge when neural agents are jointly trained to solve tasks requiring communication through a discrete channel. We investigate here the information-theoretic complexity of such…

Computation and Language · Computer Science 2020-06-29 Eugene Kharitonov , Rahma Chaabouni , Diane Bouchacourt , Marco Baroni

By 'informational entropy', we understand an inherent boundary to knowability, due e.g. to perceptual, theoretical, evidential or linguistic limits. In this paper, we discuss a logical framework in which this boundary is incorporated into…