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Although most theories posit that natural behavior can be explained as maximizing some form of extrinsic reward, often called utility, some behaviors appear to be reward independent. For instance, spontaneous motor babbling in human…

Neurons and Cognition · Quantitative Biology 2026-01-16 Rubén Moreno-Bote , Ralf Haefner , Jordi Galiano-Landeira , Tianming Yang , Pedro Maldonado

A new theory of motivations, emotions and attention is suggested, considering them as functions of sensory systems. The theory connects neurophysiological mechanisms of mental phenomena with the change of metabolic and functional state of…

Neurons and Cognition · Quantitative Biology 2011-11-15 Sergey E. Murik

The ability to interpret the mental state of another agent based on its behavior, also called Theory of Mind (ToM), is crucial for humans in any kind of social interaction. Artificial systems, such as intelligent assistants, would also…

Artificial Intelligence · Computer Science 2019-09-24 Jan Pöppel , Stefan Kopp

This survey contains a selection of topics unified by the concept of positive semi-definiteness (of matrices or kernels), reflecting natural constraints imposed on discrete data (graphs or networks) or continuous objects (probability or…

Classical Analysis and ODEs · Mathematics 2019-11-13 Alexander Belton , Dominique Guillot , Apoorva Khare , Mihai Putinar

The paper studies the complexity of the optimization problem behind the Model-Agnostic Meta-Learning (MAML) algorithm. The goal of the study is to determine the global convergence of MAML on sequential decision-making tasks possessing a…

Machine Learning · Computer Science 2020-12-14 Igor Molybog , Javad Lavaei

A class of background independent membrane field theories are studied, and several properties are discovered which suggest that they may play a role in a background independent form of M theory. The bulk kinematics of these theories are…

High Energy Physics - Theory · Physics 2014-11-18 Lee Smolin

Model-independent search strategies have been increasingly proposed in recent years because on the one hand there has been no clear signal for new physics and on the other hand there is a lack of a highly probable and parameter-free…

High Energy Physics - Phenomenology · Physics 2023-03-22 Sascha Caron , Roberto Ruiz de Austri , Zhongyi Zhang

Supersymmetry is one of the most plausible and theoretically motivated frameworks for extending the Standard Model. However, any supersymmetry in Nature must be a broken symmetry. Dynamical supersymmetry breaking (DSB) is an attractive idea…

High Energy Physics - Theory · Physics 2008-11-26 Yael Shadmi , Yuri Shirman

Land management intensity shapes ecosystem service provision, socio-ecological resilience and is central to sustainable transformation. Yet most land use models emphasise economic and biophysical drivers, while socio-psychological factors…

Computational Engineering, Finance, and Science · Computer Science 2026-02-11 Ronja Hotz , Calum Brown , Yongchao Zeng , Thomas Schmitt , Mark Rounsevell

Machine learning methods have been remarkably successful for a wide range of application areas in the extraction of essential information from data. An exciting and relatively recent development is the uptake of machine learning in the…

Machine Learning · Computer Science 2020-03-13 Ribana Roscher , Bastian Bohn , Marco F. Duarte , Jochen Garcke

Individual choices often depend on the order in which the decisions are made. In this paper, we expose a general theory of measurable systems (an example of which is an individual's preferences) allowing for incompatible (non-commuting)…

Physics and Society · Physics 2007-06-20 V. I. Danilov , A. Lambert-Mogiliansky

Large Language Models(LLMs) have revolutionized various applications in natural language processing (NLP) by providing unprecedented text generation, translation, and comprehension capabilities. However, their widespread deployment has…

Computation and Language · Computer Science 2024-09-26 Rajesh Ranjan , Shailja Gupta , Surya Narayan Singh

How can cognitive science build generalizable theories that span the full scope of natural situations and behaviors? We argue that progress in Artificial Intelligence (AI) offers timely opportunities for cognitive science to embrace…

Neurons and Cognition · Quantitative Biology 2026-05-25 Wilka Carvalho , Andrew Lampinen

Making a survey of recent constructions of universal cohomologies we suggest a new framework for a theory of motives in algebraic geometry.

Algebraic Geometry · Mathematics 2025-01-31 L. Barbieri-Viale

LLMs are increasingly used to support qualitative research, yet existing systems produce outputs that vary widely--from trace-faithful summaries to theory-mediated explanations and system models. To make these differences explicit, we…

Computation and Language · Computer Science 2026-01-21 Xinyu Pi , Qisen Yang , Chuong Nguyen , Hua Shen

We review our most recent results in formulating gauge theories in the presence of a background field on the basis of symmetry arguments only. In particular we show how one can gain full control over the dependence on the background field…

High Energy Physics - Theory · Physics 2014-01-16 Daniele Binosi

We develop new tools to study landscapes in nonconvex optimization. Given one optimization problem, we pair it with another by smoothly parametrizing the domain. This is either for practical purposes (e.g., to use smooth optimization…

Optimization and Control · Mathematics 2024-03-05 Eitan Levin , Joe Kileel , Nicolas Boumal

The paper discusses fundamental problems in mathematical description of social systems based on physical concepts, with so-called statistical social systems being the main subject of consideration. Basic properties of human beings and human…

Physics and Society · Physics 2011-04-11 Ihor Lubashevsky , Natalia Plawinska

In this article a sequential theory in the category of spaces and proper maps is described and developed. As a natural extension a sequential theory for exterior spaces and maps is obtained.

Category Theory · Mathematics 2007-11-05 L. Espanol , J. M. Garcia Calcines , M. C. Minguez

My doctoral research focuses on understanding semantic knowledge in neural network models trained solely to predict natural language (referred to as language models, or LMs), by drawing on insights from the study of concepts and categories…

Computation and Language · Computer Science 2021-11-05 Kanishka Misra