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One of the greatest research challenges of this century is to understand the neural basis for how behavior emerges in brain-body-environment systems. To this end, research has flourished along several directions but have predominantly…

Neurons and Cognition · Quantitative Biology 2021-06-10 Madhavun Candadai

As artificial intelligence systems (AIs) become increasingly produced by recursive self-improvement, a form of evolution may emerge, with the traits of AI systems shaped by the success of earlier AIs in designing and propagating their…

Artificial Intelligence · Computer Science 2026-04-14 Kenneth D Harris

We propose a novel evolutionary algorithm on bit vectors which derives from the principles of information theory. The information-theoretic evolutionary algorithm (it-EA) iteratively updates a search distribution with two parameters, the…

Neural and Evolutionary Computing · Computer Science 2023-04-13 Arnaud Berny

A novel Markovian network evolution model is introduced and analysed by means of information theory. It will be proved that the model, called Network Evolution Chain, is a stationary and ergodic stochastic process. Therefore, the Asymptotic…

Information Theory · Computer Science 2022-01-21 Amirmohammad Farzaneh , Justin P. Coon

The purpose of this Note is twofold: First, we introduce the general formalism of evolutionary genetics dynamics involving fitnesses, under both the deterministic and stochastic setups, and chiefly in discrete-time. In the process, we…

Quantitative Methods · Quantitative Biology 2015-05-14 Thierry Huillet

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

In some estimation problems, especially in applications dealing with information theory, signal processing and biology, theory provides us with additional information allowing us to restrict the parameter space to a finite number of points.…

Methodology · Statistics 2012-07-25 Christine Choirat , Raffaello Seri

The Fisher information matrix can be used to characterize the local geometry of the parameter space of neural networks. It elucidates insightful theories and useful tools to understand and optimize neural networks. Given its high…

Machine Learning · Computer Science 2024-10-31 Alexander Soen , Ke Sun

Biological data objects often have both of the following features: (i) they are functions rather than single numbers or vectors, and (ii) they are correlated due to phylogenetic relationships. In this paper we give a flexible statistical…

Quantitative Methods · Quantitative Biology 2012-12-20 Nick S. Jones , John Moriarty

Fisher information and Shannon entropy are fundamental tools for understanding and analyzing dynamical systems from complementary perspectives. They can characterize unknown parameters by quantifying the information contained in variables,…

Information Theory · Computer Science 2025-12-19 Yuxuan Bao , J. Nathan Kutz

Understanding the evolution of binary traits, which affects the birth and survival of species and also the rate of molecular evolution, remains challenging. A typical example is the evolution of mating systems in plant species. In this…

Populations and Evolution · Quantitative Biology 2017-04-04 Daniah Tahir , Sylvain Glémin , Martin Lascoux , Ingemar Kaj

We provide an information-theoretic analysis of Thompson sampling that applies across a broad range of online optimization problems in which a decision-maker must learn from partial feedback. This analysis inherits the simplicity and…

Machine Learning · Computer Science 2015-06-09 Daniel Russo , Benjamin Van Roy

The network information system is a military information network system with evolution characteristics. Evolution is a process of replacement between disorder and order, chaos and equilibrium. Given that the concept of evolution originates…

Neural and Evolutionary Computing · Computer Science 2020-02-25 Tingting Zhang , Yushi Lan , Aiguo Song , Kun Liu , Nan Wang

Mathematical theory of selection is developed within the frameworks of general models of inhomogeneous populations with continuous time. Methods that allow us to study the distribution dynamics under natural selection and to construct…

Populations and Evolution · Quantitative Biology 2009-12-22 Georgy P. Karev

Computer modelling for evolutionary systems consists in: 1) to store in the memory the individual features of each member of a large population; and 2) to update the whole system repeatedly, as time goes by, according to some prescribed…

Statistical Mechanics · Physics 2007-05-23 Paulo Murilo Castro de Oliveira

Identification of taxa can significantly be assisted by statistical classification based on trait measurements in two major ways; either individually or by phylogenetic (clustering) methods. In this paper we present a general Bayesian…

Applications · Statistics 2021-09-17 Måns Karlsson , Ola Hössjer

Evolutionary branching is analysed in a stochastic, individual-based population model under mutation and selection. In such models, the common assumption is that individual reproduction and life career are characterised by values of a…

Populations and Evolution · Quantitative Biology 2025-10-01 S. Sagitov , B. Mehlig , P. Jagers , V. Vatutin

The Darwinian paradigm of biological evolution is based on the separability of the variation and selection processes. As a result, the population thinking had always been an integral part of the Darwinian approach. I propose an alternative…

Other Quantitative Biology · Quantitative Biology 2007-05-23 Vasily Ogryzko

The theory of natural selection has two forms. Deductive theory describes how populations change over time. One starts with an initial population and some rules for change. From those assumptions, one calculates the future state of the…

Populations and Evolution · Quantitative Biology 2016-11-15 Steven A. Frank

The behavior of ecological systems mainly relies on the interactions between the species it involves. We consider the problem of inferring the species interaction network from abundance data. To be relevant, any network inference…

Applications · Statistics 2019-10-29 Raphaëlle Momal , Stéphane Robin , Christophe Ambroise