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This note continues paper of Denisov and Wachtel (2010), where we have constructed a $k$-dimensional random walk conditioned to stay in the Weyl chamber of type $A$. The construction was done under the assumption that the original random…

Probability · Mathematics 2011-03-24 Denis Denisov , Vitali Wachtel

The first passage time process of a L\'evy subordinator with heavy-tailed L\'evy measure has long-range dependent paths. The random fluctuations that appear under two natural schemes of summation and time scaling of such stochastic…

Probability · Mathematics 2012-04-02 Ingemar Kaj , Anders Martin-Löf

Evolutionary algorithms, inspired by natural evolution, aim to optimize difficult objective functions without computing derivatives. Here we detail the relationship between population genetics and evolutionary optimization and formulate a…

Populations and Evolution · Quantitative Biology 2023-07-19 Jakub Otwinowski , Colin LaMont

We introduce a persistent random walk model with finite velocity and self-reinforcing directionality, which explains how exponentially distributed runs self-organize into truncated L\'evy walks observed in active intracellular transport by…

Statistical Mechanics · Physics 2024-02-07 Daniel Han , Marco A. A. da Silva , Nickolay Korabel , Sergei Fedotov

With the rapid increase of valuable observational, experimental and simulated data for complex systems, much efforts have been devoted to identifying governing laws underlying the evolution of these systems. Despite the wide applications of…

Machine Learning · Statistics 2021-10-01 Yang Li , Yubin Lu , Shengyuan Xu , Jinqiao Duan

Random walks are powerful tools to analyze spatial-temporal patterns produced by living organisms ranging from cells to humans. At the same time, it is evident that these patterns are not completely random but are results of a convolution…

Statistical Mechanics · Physics 2021-12-08 M. I. Krivonosov , S. N. Tikhomirov , S. Denisov

In this paper, we intend to formulate a new metaheuristic algorithm, called Cuckoo Search (CS), for solving optimization problems. This algorithm is based on the obligate brood parasitic behaviour of some cuckoo species in combination with…

Optimization and Control · Mathematics 2020-07-17 Xin-She Yang , Suash Deb

The L\'evy walk process for the lower interval of the time of flight distribution ($\alpha<1$) and with finite resting time between consecutive flights is discussed. The motion is restricted to a region bounded by two absorbing barriers and…

Statistical Mechanics · Physics 2023-07-19 A. Kamińska , T. Srokowski

Using data on the Berlin public transport network, the present study extends previous observations of fractality within public transport routes by showing that also the distribution of inter-station distances along routes displays…

Physics and Society · Physics 2015-07-02 C. von Ferber , Yu. Holovatch

We investigate the emergence of self-organised trails between two specific target areas in collective motion of social organisms by means of an agent-based model. We present numerical evidences that an increase in the efficiency of…

Adaptation and Self-Organizing Systems · Physics 2018-02-27 E. Brigatti , A. Hernández

Molecular search phenomena are observed in a variety of chemical and biological systems. During the search the participating particles frequently move in complex inhomogeneous environments with random transitions between different dynamic…

Statistical Mechanics · Physics 2018-11-13 Jaeoh Shin , Anatoly B. Kolomeisky

Slow self-avoiding adaptive walks by an infinite radius search algorithm (Limax) are analyzed as themselves, and as the network they form. The study is conducted on several NK problems and two HIFF problems. We find that examination of such…

Neural and Evolutionary Computing · Computer Science 2011-07-20 Susan Khor

For a random walk defined for a doubly infinite sequence of times, we let the time parameter itself be an integer-valued process, and call the orginal process a random walk at random time. We find the scaling limit which generalizes the…

Probability · Mathematics 2013-07-30 Paul Jung , Greg Markowsky

L\'evy walk process is one of the most effective models to describe superdiffusion, which underlies some important movement patterns and has been widely observed in the micro and macro dynamics. From the perspective of random walk theory,…

Statistical Mechanics · Physics 2021-04-07 Tian Zhou , Pengbo Xu , Weihua Deng

Although stochastic optimization is central to modern machine learning, the precise mechanisms underlying its success, and in particular, the precise role of the stochasticity, still remain unclear. Modelling stochastic optimization…

Machine Learning · Statistics 2020-06-12 Liam Hodgkinson , Michael W. Mahoney

Order can spontaneously emerge from seemingly noisy interactions between biological agents, like a flock of birds changing their direction of flight in unison, without a leader or an external cue. We are interested in the generic conditions…

Biological Physics · Physics 2021-03-09 Carsten T. van de Kamp , George Dadunashvili , Johan L. A. Dubbeldam , Timon Idema

Our study focuses on analyzing the behavior of a stochastic predator-prey model with a time delay and logistic growth of prey, influenced by L\'{e}vy noise. Initially, we establish the existence, uniqueness, and boundedness of a positive…

Dynamical Systems · Mathematics 2023-04-26 Jaouad Danane , Delfim F. M. Torres

We present a simple paradigm for detection of an immobile target by a space-time coupled random walker with a finite lifetime. The motion of the walker is characterized by linear displacements at a fixed speed and exponentially distributed…

Statistical Mechanics · Physics 2015-06-10 D. Campos , E. Abad , V. Méndez , S. B. Yuste , K. Lindenberg

Interest in multimodal function optimization is expanding rapidly since real world optimization problems often demand locating multiple optima within a search space. This article presents a new multimodal optimization algorithm named as the…

Neural and Evolutionary Computing · Computer Science 2014-07-01 Erik Cuevas , Mauricio Gonzalez

Natural gradient descent is an optimization method traditionally motivated from the perspective of information geometry, and works well for many applications as an alternative to stochastic gradient descent. In this paper we critically…

Machine Learning · Computer Science 2020-09-22 James Martens
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