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Symbolic regression is a powerful system identification technique in industrial scenarios where no prior knowledge on model structure is available. Such scenarios often require specific model properties such as interpretability, robustness,…

In this paper, we construct a new unpredictable function. Our approach is based on adapting the concept of symbolic dynamics to introduce a map on the space of infinite sequences generated by the discrete distribution. We show that there…

Dynamical Systems · Mathematics 2020-04-21 Marat Akhmet , Mehmet Onur Fen , Ejaily Milad Alejaily

The thesis is devoted to relations between algebra and symbolic dynamics. Various generalisations of sturmian sequences are discoursed. Let $W$ be an infinite word over a finite alphabet $A$. The combinatorial criteria of existence of…

Dynamical Systems · Mathematics 2015-12-22 Alexander Chernyatiev

We develop a theoretical framework that explains how discrete symbolic structures can emerge naturally from continuous neural network training dynamics. By lifting neural parameters to a measure space and modeling training as Wasserstein…

Machine Learning · Computer Science 2025-07-03 Peihao Wang , Zhangyang Wang

We investigate the iterative construction of discrete Laplacians on 2D square lattices, revealing emergent fractal-like patterns shaped by modular arithmetic. While classical 2222-style iterations reproduce known structures such as the…

Dynamical Systems · Mathematics 2026-03-16 Małgorzata Nowak-Kępczyk

Recent work has attempted to characterize the structure of semantic memory and the search algorithms which, together, best approximate human patterns of search revealed in a semantic fluency task. There are a number of models that seek to…

Computation and Language · Computer Science 2017-12-01 Filip Miscevic , Aida Nematzadeh , Suzanne Stevenson

Symbolic regression is a type of discrete optimization problem that involves searching expressions that fit given data points. In many cases, other mathematical constraints about the unknown expression not only provide more information…

Machine Learning · Computer Science 2021-02-16 Li Li , Minjie Fan , Rishabh Singh , Patrick Riley

Contrary to the established view of the Lorenz system as an archetype of dissipative chaos lacking conserved quantities, this work rigorously demonstrates the existence of a novel class of history-dependent dynamical invariants. Through a…

Chaotic Dynamics · Physics 2025-11-11 B. A. Toledo

In this article we show how ideas, methods and results from optimal transportation can be used to study various aspects of the stationary measuresof Iterated Function Systems equipped with a probability distribution. We recover a classical…

Classical Analysis and ODEs · Mathematics 2021-06-02 Benoît Kloeckner

This chapter presents some of the links between automata theory and symbolic dynamics. The emphasis is on two particular points. The first one is the interplay between some particular classes of automata, such as local automata and results…

Formal Languages and Automata Theory · Computer Science 2011-02-08 Marie-Pierre Béal , Jean Berstel , Søren Eilers , Dominique Perrin

Starting with a combinatorial partition theorem for words over an infinite alphabet dominated by a fixed sequence, established recently by the authors, we prove recurrence results for topological dynamical systems indexed by such words. In…

General Topology · Mathematics 2011-01-18 Vassiliki Farmaki , Andreas Koutsogiannis

A prototypical example of categorial grammars are those based on Lambek calculus, i.e. noncommutative intuitionistic linear logic. However, it has been noted that purely noncommutative operations are often not sufficient for modeling even…

Logic · Mathematics 2025-07-16 Sergey Slavnov

We present Dynamic Epistemic Temporal Logic, a framework for reasoning about operations on multi-agent Kripke models that contain a designated temporal relation. These operations are natural extensions of the well-known "action models" from…

Logic in Computer Science · Computer Science 2014-11-25 Bryan Renne , Joshua Sack , Audrey Yap

We propose a symbolic generative task description language and a corresponding inference engine capable of representing arbitrary multimodal tasks as structured symbolic flows. Unlike conventional generative models that rely on large-scale…

We study a deterministic dynamics with two time scales in a continuous state attractor network. To the usual (fast) relaxation dynamics towards point attractors (``patterns'') we add a slow coupling dynamics that makes the visited patterns…

Neurons and Cognition · Quantitative Biology 2010-06-10 Juliana R. Dias , Rodrigo F. Oliveira , Osame Kinouchi

In this article, we define a very important sequence of functions, all the functions of this sequence present behaviors very close to that of the Collatz function. The study of such functions allows us to obtain very interesting results…

General Mathematics · Mathematics 2021-07-13 Raouf Rajab

Many real-world systems give rise to a time series of symbols. The elements in a sequence can be generated by agents walking over a networked space so that whenever a node is visited the corresponding symbol is generated. In many situations…

Social and Information Networks · Computer Science 2022-11-15 Lucas Guerreiro , Filipi N. Silva , Diego R. Amancio

Animals flexibly recombine a finite set of core motor motifs to meet diverse task demands, but existing behavior segmentation methods oversimplify this process by imposing discrete syllables under restrictive generative assumptions. To…

Machine Learning · Computer Science 2026-02-27 Jiyi Wang , Jingyang Ke , Bo Dai , Anqi Wu

A general procedure which defines a partial ordering of cyclic permutations induced by continuous maps is known for constructing immediate successors to a cycle. We expound on this procedure in terms of labelled digraphs and characteristic…

Dynamical Systems · Mathematics 2019-10-08 Yoshifumi Takenouchi , Richell Celeste

We present a probabilistic generative model for inferring a description of coordinated, recursively structured group activities at multiple levels of temporal granularity based on observations of individuals' trajectories. The model…

Artificial Intelligence · Computer Science 2016-04-26 Ernesto Brau , Colin Dawson , Alfredo Carrillo , David Sidi , Clayton T. Morrison