Sex as Gibbs Sampling: a probability model of evolution (original) (raw)

Evolutionary implementation of Bayesian computations

Eors Szathmary

2019

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Evolutionary Markov Chain Monte Carlo

Madalina Drugan

Lecture Notes in Computer Science, 2004

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Toward a unifying framework for evolutionary processes

Per Kristian Lehre

Journal of theoretical biology, 2015

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A Markov chain model of evolution in asexually reproducing populations: insight and analytical tractability in the evolutionary process

Jerome Paul

Cornell University - arXiv, 2013

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Efficient algorithms for inverting evolution

Sampath Kannan

Journal of the ACM, 1999

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Recombination operators and selection strategies for evolutionary Markov Chain Monte Carlo algorithms

Madalina Drugan

Evolutionary intelligence, 2010

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Geometrical Recombination Operators for Real-Coded Evolutionary MCMCs

Madalina Drugan

Evolutionary Computation, 2010

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A review on probabilistic graphical models in evolutionary computation

Concha Bielza

2012

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The evolution of learning systems: to Bayes or not to be

Nestor Caticha

2006

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Benefits of Sexual Reproduction in Evolutionary Computation

Madeleine Friedrich

2013

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Limits On The Information Acquired By An Evolving Population

Christopher Rose

arXiv (Cornell University), 2022

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A Unified Bayesian Framework for Evolutionary Learning and Optimization

Byoungtak Zhang

Natural Computing Series, 2003

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An alternative explanation for the manner in which genetic algorithms operate

Hans-Georg Beyer

Biosystems, 1997

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LEARNABLE EVOLUTION MODEL: Evolutionary Processes Guided by Machine Learning

Floriana Esposito

Ml, 2000

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Algorithmically probable mutations reproduce aspects of evolution such as convergence rate, genetic memory, and modularity

Santiago Hernández Orozco

arXiv (Cornell University), 2017

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Finite Markov chain analysis of genetic algorithms

Jeffrey Horn

… Genetic Algorithms on Genetic algorithms …

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Genetic and Evolutionary Computation – GECCO 2004

Pier Luca Lanzi

Lecture Notes in Computer Science, 2004

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An alternative measurement of the entropy evolution of a genetic algorithm

Manuel Alfonseca

2009

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Algorithmically probable mutations reproduce aspects of evolution such as convergence rate, genetic memory, modularity, diversity explosions, and mass extinction

Santiago Hernández Orozco

arXiv (Cornell University), 2017

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Exploiting Quotients of Markov Chains to Derive Properties of the Stationary Distribution of the Markov Chain Associated to an Evolutionary Algorithm

Lothar M Schmitt

Lecture Notes in Computer Science, 2006

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Reducing model complexity of the general Markov model of evolution

Faisal Ababneh

2011

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Evolutionary Computation - A Study on Collective Learning

Hans-Paul Schwefel

2000

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Simulated Evolution and Learning

Arnab Bhattacharya

Lecture Notes in …, 2010

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Entropic sampling and natural selection in biological evolution

Doochul Kim

Journal of Physics A: Mathematical and General, 1997

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Hidden Markov Dirichlet process: modeling genetic inference in open ancestral space

Kyung-Ah Sohn

Bayesian Analysis, 2007

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A Bayesian Approach to Inferring Rates of Selfing and Locus-Specific Mutation

Ann Sakai

Genetics, 2015

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Random Evolutionary Dynamics Driven by Fitness and House-of-Cards Mutations: Sampling Formulae

Thierry Huillet

Journal of Statistical Physics

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Smoothing representation of fitness landscapes - the genotype-phenotype map of evolution

Torsten Asselmeyer-Maluga

Eprint Arxiv Adap Org 9508002, 1995

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On sampling error in evolutionary algorithms

Franz Rothlauf

Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2021

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Major evolutionary transitions as Bayesian structure learning

Eors Szathmary

2018

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