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Computer simulations are an important tool for studying the mechanics of biological evolution. In particular, in silico work with agent-based models provides an opportunity to collect high-quality records of ancestry relationships among…

Neural and Evolutionary Computing · Computer Science 2024-10-03 Matthew Andres Moreno , Anika Ranjan , Emily Dolson , Luis Zaman

At computer modeling of process of training it is usually supposed that all elements of a training material are forgotten with an identical speed. But in practice that knowledge which are included in educational activity of the pupil are…

Computers and Society · Computer Science 2014-01-14 Robert V. Mayer

In modern science, computer models are often used to understand complex phenomena, and a thriving statistical community has grown around analyzing them. This review aims to bring a spotlight to the growing prevalence of stochastic computer…

Time-dependent data often exhibit characteristics, such as non-stationarity and heavy-tailed errors, that would be inappropriate to model with the typical assumptions used in popular models. Thus, more flexible approaches are required to be…

Machine Learning · Statistics 2023-11-02 Taole Sha , Michael Minyi Zhang

Statistical and computational methods are widely used in today's scientific studies. Using a female fertility potential in childhood cancer survivors as an example, we illustrate how these methods can be used to extract insight regarding…

Applications · Statistics 2020-11-20 L. Yu , Z. Lu , P. C. Nathan , S. Mostoufi-Moab , Y. Yuan

This article presents an educational proposal based on the computational implementation of a model of interaction between particles of different types, as a tool for the development of STEM (Science, Technology, Engineering, and…

Physics Education · Physics 2025-03-12 Matías Hernández

Understanding the pattern formation in communities has been at the center of attention in various fields. Here we introduce a novel model, called an "information-particle model," which is based on the reaction-diffusion model and the…

Physics and Society · Physics 2023-07-21 Junichi Miyakoshi

This chapter discusses the possibility of instilling a virtual world with mechanisms for evolution and natural selection in order to generate rich ecosystems of complex organisms in a process akin to biological evolution. Some previous work…

Neural and Evolutionary Computing · Computer Science 2018-06-05 Tim Taylor

Provided that there is no theoretical frame for complex engineered systems (CES) as yet, this paper claims that bio-inspired engineering can help provide such a frame. Within CES bio-inspired systems play a key role. The disclosure from…

Other Computer Science · Computer Science 2011-10-18 Nelson Alfonso Gómez-Cruz , Carlos Eduardo Maldonado

Mathematical models play an increasingly important role in the interpretation of biological experiments. Studies often present a model that generates the observations, connecting hypothesized process to an observed pattern. Such generative…

Populations and Evolution · Quantitative Biology 2014-06-18 Steven A. Frank

Learning and the ability to learn are important factors in development and evolutionary processes [1]. Depending on the level, the complexity of learning can strongly vary. While associative learning can explain simple learning behaviour…

Neurons and Cognition · Quantitative Biology 2007-05-23 Reimer Kuehn , Ion-Olimpiu Stamatescu

The possibility that evolutionary forces -- together with a few fundamental factors such as thermodynamic constraints, specific computational features enabling information processing, and ecological processes -- might constrain the logic of…

Biological Physics · Physics 2025-12-30 Manlio De Domenico

Computational modelling with multi-agent systems is becoming an important technique of studying language evolution. We present a brief introduction into this rapidly developing field, as well as our own contributions that include an…

Physics and Society · Physics 2010-08-24 Adam Lipowski , Dorota Lipowska

Machine learning is a computational process. To that end, it is inextricably tied to computational power - the tangible material of chips and semiconductors that the algorithms of machine intelligence operate on. Most obviously,…

Artificial Intelligence · Computer Science 2018-03-28 Tim Hwang

Algorithms deployed in education can shape the learning experience and success of a student. It is therefore important to understand whether and how such algorithms might create inequalities or amplify existing biases. In this paper, we…

Computers and Society · Computer Science 2022-12-21 Jade Maï Cock , Muhammad Bilal , Richard Davis , Mirko Marras , Tanja Käser

Human-AI coevolution, defined as a process in which humans and AI algorithms continuously influence each other, increasingly characterises our society, but is understudied in artificial intelligence and complexity science literature.…

Genetic Programming is an evolutionary algorithm that generates computer programs, or mathematical expressions, to solve complex problems. In this Guide, we demonstrate how to use Genetic Programming to develop surrogate models to mitigate…

What does it mean to claim that a physical or natural system computes? One answer, endorsed here, is that computing is about programming a system to behave in different ways. This paper offers an account of what it means for a physical…

Information Theory · Computer Science 2013-06-18 Hector Zenil

In bacterial populations, cells are able to cooperate in order to yield complex collective functionalities. Interest in population-level cellular behaviour is increasing, due to both our expanding knowledge of the underlying biological…

Multiagent Systems · Computer Science 2012-11-07 Angel Goni-Moreno , Martyn Amos

We present an algorithm for the stochastic simulation of gene expression and heterogeneous population dynamics. The algorithm combines an exact method to simulate molecular-level fluctuations in single cells and a constant-number Monte…

Computational Physics · Physics 2016-08-24 Daniel A. Charlebois , Jukka Intosalmi , Dawn Fraser , Mads Kaern