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Related papers: Mass redistribution in variable mass systems

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Inverse reinforcement learning is the problem of inferring a reward function from an optimal policy or demonstrations by an expert. In this work, it is assumed that the reward is expressed as a reward machine whose transitions depend on…

Machine Learning · Computer Science 2025-10-23 Mohamad Louai Shehab , Antoine Aspeel , Necmiye Ozay

Suppose that in the four tests Alice's scores are 90, 95, 85, 90, and Bob's scores are 85, 95, 90, 90. How to evaluate their scores? In this paper, we introduce the concept of ordered probability mass function which can be used to find a…

Discrete Mathematics · Computer Science 2013-09-06 Zhengjun Cao , Lihua Liu

This paper introduces a new technique for learning probabilistic models of mass and friction distributions of unknown objects, and performing robust sliding actions by using the learned models. The proposed method is executed in two…

Robotics · Computer Science 2020-08-06 Changkyu Song , Abdeslam Boularias

This paper discusses and summarizes some results on complex variables that are very useful in fractional-order systems analysis and design, specifically when the system is analyzed in the frequency domain. The author hopes that this…

Signal Processing · Electrical Eng. & Systems 2026-03-26 Emmanuel A. Gonzalez

We investigate optimal mass transport problem of affine-nonlinear dynamical systems with input and density constraints. Three algorithms are proposed to tackle this problem, including two Uzawa-type methods and a splitting algorithm based…

Optimization and Control · Mathematics 2024-03-26 Dongjun Wu , Anders Rantzer

We introduce a new dynamical system, at the interface between second-order dynamics with inertia and Newton's method. This system extends the class of inertial Newton-like dynamics by featuring a time-dependent parameter in front of the…

Optimization and Control · Mathematics 2024-02-13 Camille Castera , Hedy Attouch , Jalal Fadili , Peter Ochs

This paper presents a reduced-order model for the Reynolds equation for deformable structure and large displacements. It is based on the model established in [11] which is piece-wise linearized using two different methods. The advantages…

Other Computer Science · Computer Science 2009-11-13 A. Missoffe , J. Juillard , Denis Aubry

We study the distributions of money in a simple closed economic system for different types of monetary transactions. We know that for arbitrary and random sharing but locally conserving money transactions, the money distribution goes to the…

Statistical Mechanics · Physics 2009-11-07 Anirban Chakraborti

The method of factorization, based on the model of unstable particles with a smeared mass, is applied to the processes with an unstable particle in the intermediate state. It was shown, that in the framework of the method suggested, the…

High Energy Physics - Phenomenology · Physics 2010-04-15 V. I. Kuksa

A new type of elasticity of random (multifractal) structures is suggested. A closed system of constitutive equations is obtained on the basis of two proposed phenomenological laws of reversible deformations of multifractal structures. The…

Materials Science · Physics 2007-05-23 Alexander S. Balankin

Factorization machines (FMs) are a powerful tool for regression and classification in the context of sparse observations, that has been successfully applied to collaborative filtering, especially when side information over users or items is…

Machine Learning · Computer Science 2022-12-21 Jill-Jênn Vie , Tomas Rigaux , Hisashi Kashima

We present a physical model for turbulent friction on rough surfaces with regularly distributed roughness elements. Wall shear stresses are expressed as functions of physical quantities. Surfaces with varying roughness densities and…

Fluid Dynamics · Physics 2016-10-24 Zhuoqun Li , Xiaojing Zheng

Flux reconstruction provides a framework for solving partial differential equations in which functions are discontinuously approximated within elements. Typically, this is done by using polynomials. Here, the use of radial basis functions…

Numerical Analysis · Mathematics 2022-01-06 Rob Watson , Will Trojak

A simple model accounting for the ejection of heavy particles from the vortical structures of a turbulent flow is introduced. This model involves a space and time discretization of the dynamics and depends on only two parameters: the…

Chaotic Dynamics · Physics 2009-11-13 Jeremie Bec , Raphael Chetrite

In this work we present a generalised viscoelastic model using distributed-order derivatives. The model consists of two distributed-order elements (distributed springpots) connected in series, as in the Maxwell model. The new model…

Classical Physics · Physics 2022-12-28 Luis Ferrás , Maria Luisa Morgado , Magda Rebelo

We consider the vertical motion of a free falling ball bouncing elastically on a racket moving in the vertical direction according to a regular periodic function $f$. We give a sufficient condition on the second derivative of $f$ giving…

Dynamical Systems · Mathematics 2020-06-11 Stefano Marò

Latent force models are a class of hybrid models for dynamic systems, combining simple mechanistic models with flexible Gaussian process (GP) perturbations. An extension of this framework to include multiplicative interactions between the…

Machine Learning · Statistics 2019-01-01 Daniel J. Tait , Bruce J. Worton

This paper is a preliminary work to address the problem of dynamical systems with parameters varying in time. An idea to predict their behaviour is proposed. These systems are called \emph{transient systems}, and are distinguished from…

Dynamical Systems · Mathematics 2014-11-04 Ugo Galvanetto , Luca Magri

Resonance-mediated many body decays of heavy mesons are analyzed. We focus on some particular processes, in which the available phase space for the decay of the intermediate resonance is very narrow. It is shown that the mass selection…

High Energy Physics - Phenomenology · Physics 2007-05-23 L. N. Epele , D. Gomez Dumm , R. Mendez-Galain , A. Szynkman

A new approach for efficiently exploring the configuration space and computing the free energy of large atomic and molecular systems is proposed, motivated by an analogy with reinforcement learning. There are two major components in this…

Chemical Physics · Physics 2018-04-18 Linfeng Zhang , Han Wang , Weinan E
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