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Multi-scale structures are prevalent in both natural and artificial systems, as they can handle increasing complexity. Several terms are employed almost interchangeably across various application domains to refer to the multi-scale concept…

Systems and Control · Electrical Eng. & Systems 2021-06-04 Ada Diaconescu , Louisa Jane Di Felice , Patricia Mellodge

Social dilemmas are situations where groups of individuals can benefit from mutual cooperation but conflicting interests impede them from doing so. This type of situations resembles many of humanity's most critical challenges, and…

Machine Learning · Computer Science 2023-05-22 Manuel Rios , Nicanor Quijano , Luis Felipe Giraldo

The universe is things which change and called events. The events are matter and field. A boundary divides a system to things and environment. The things belong to the environment have no significant effect on the things belong to the…

General Physics · Physics 2025-08-19 Hamidreza Simchi

We propose a categorical framework to reason about scientific explanations: descriptions of a phenomenon meant to translate it into simpler terms, or into a context that has been already understood. Our motivating examples come from systems…

Logic in Computer Science · Computer Science 2023-08-01 Leo Lobski , Fabio Zanasi

The Randall-Sundrum warped braneworld model is generalised to six and higher dimensions such that the warping has a non-trivial dependence on more than one dimension. This naturally leads to a brane-box like configuration alongwith scalar…

High Energy Physics - Theory · Physics 2008-11-26 Debajyoti Choudhury , Soumitra SenGupta

Cities are some of the most intricate and advanced creations of humanity. Most objects in cities are perfectly synchronised to coordinate activities such as jobs, education, transportation, entertainment, and waste management. Although each…

Physics and Society · Physics 2026-04-01 Rafael Prieto-Curiel

Large Language Models (LLMs) possess general world knowledge but often struggle to generate precise predictions in structured, domain-specific contexts such as simulations. These limitations arise from their inability to ground their broad,…

Artificial Intelligence · Computer Science 2026-01-30 Guillaume Levy , Cedric Colas , Pierre-Yves Oudeyer , Thomas Carta , Clement Romac

Modeling is a central concern in both science and engineering. However, we need a new fundamental theory to address the challenges of the digital age. In this paper, we first explain why modeling is fundamental and which challenges must be…

Software Engineering · Computer Science 2025-08-28 Peter Fettke , Wolfgang Reisig

I survey physics theories involving parallel universes, which form a natural four-level hierarchy of multiverses allowing progressively greater diversity. Level I: A generic prediction of inflation is an infinite ergodic universe, which…

Astrophysics · Physics 2007-05-23 Max Tegmark

In this paper, we suppose that the universe has an information processing layer, which coveys the informational contents accompanying the physical events. In this manner, universe is considered to be composed of several associative layers…

General Physics · Physics 2010-11-11 Baris Baykant Alagoz

On the basis that the universe is a closed quantum system with no external observers, we propose a paradigm in which the universe jumps through a series of stages. Each stage is defined by a quantum state, an information content, and rules…

Quantum Physics · Physics 2007-05-23 Jon Eakins , George Jaroszkiewicz

This book provides a completely new approach to understanding the universe. The main idea is that the principal objects in the universe form a spectrum unified by the presence of a massive or hypermassive black hole. These objects are…

Astrophysics · Physics 2019-05-30 Colin Rourke

Large language model (LLM) agents trained using reinforcement learning has achieved superhuman performance in low-cost environments like games, mathematics, and coding. However, these successes have not translated to complex domains where…

Artificial Intelligence · Computer Science 2026-02-03 Sherry Yang

The next generation of autonomous agents must not only learn efficiently but also act reliably and adapt their behavior in open worlds. Standard approaches typically assume fixed tasks and environments with little or no novelty, which…

Machine Learning · Computer Science 2026-03-02 Florent Delgrange

We define a universe as the contents of a spacetime box with comoving walls, large enough to contain essentially all phenomena that can be conceivably measured. The initial time is taken as the epoch when the lowest CMB modes undergo…

Astrophysics · Physics 2007-05-23 James D. Bjorken

Large language models (LLMs) have shown impressive capabilities across tasks such as mathematics, coding, and reasoning, yet their learning ability, which is crucial for adapting to dynamic environments and acquiring new knowledge, remains…

Computation and Language · Computer Science 2025-12-29 Zhengyu Hu , Jianxun Lian , Zheyuan Xiao , Seraphina Zhang , Tianfu Wang , Nicholas Jing Yuan , Xing Xie , Hui Xiong

The degree distribution, referred to as the delta-sequence of a network is studied. Using the non-normalized Lorenz curve, we apply a generalized form of the classical majorization partial order. Next, we introduce a new class of small…

General Mathematics · Mathematics 2024-03-28 Leo Egghe

In this paper, we propose a general framework that extends the theory of permutation patterns to higher dimensions and unifies several combinatorial objects studied in the literature. Our approach involves introducing the concept of a…

Combinatorics · Mathematics 2024-11-06 Shaoshi Chen , Hanqian Fang , Sergey Kitaev , Candice X. T. Zhang

To be robust to surprising developments, an intelligent agent must be able to respond to many different types of unexpected change in the world. To date, there are no general frameworks for defining and characterizing the types of…

Artificial Intelligence · Computer Science 2023-05-09 Matthew Molineaux , Dustin Dannenhauer , Eric Kildebeck

As deep learning systems are scaled up to many billions of parameters, relating their internal structure to external behaviors becomes very challenging. Although daunting, this problem is not new: Neuroscientists and cognitive scientists…