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The genetic code maps the sixty-four nucleotide triplets (codons) to twenty amino-acids. Some argue that the specific form of the code with its twenty amino-acids might be a 'frozen accident' because of the overwhelming effects of any…

Quantitative Methods · Quantitative Biology 2010-07-26 Tsvi Tlusty

Genetic algorithms constitute a family of black-box optimization algorithms, which take inspiration from the principles of biological evolution. While they provide a general-purpose tool for optimization, their particular instantiations can…

Neural and Evolutionary Computing · Computer Science 2023-04-11 Robert Tjarko Lange , Tom Schaul , Yutian Chen , Chris Lu , Tom Zahavy , Valentin Dalibard , Sebastian Flennerhag

Recent advances in generative AI have been largely driven by large language models (LLMs), deep neural networks that operate over discrete units called tokens. To represent text, the vast majority of LLMs use words or word fragments as the…

Gene finding is the task of identifying the locations of coding sequences within the vast amount of genetic code contained in the genome. With an ever increasing quantity of raw genome sequences, gene finding is an important avenue towards…

Genomics · Quantitative Biology 2025-05-07 Frederikke I. Marin , Dennis Pultz , Wouter Boomsma

We investigate the ability of a genetic algorithm to design cellular automata that perform computations. The computational strategies of the resulting cellular automata can be understood using a framework in which ``particles'' embedded in…

adap-org · Physics 2015-06-30 James P. Crutchfield , Melanie Mitchell , Rajarshi Das

Genetic algorithms (GAs) have a long history of over four decades. GAs are adaptive heuristic search algorithms that provide solutions for optimization and search problems. The GA derives expression from the biological terminology of…

Optics · Physics 2018-12-03 Kaspar Höschel , Vasudevan Lakshminarayanan

Many biological processes have been the source of inspiration for heuristic methods that generate high-quality solutions to solve optimization and search problems. This thesis presents an epigenetic technique for Evolutionary Algorithms,…

Neural and Evolutionary Computing · Computer Science 2021-02-22 Alvarez Lifeth

Cartesian Genetic Programming is often used with a point mutation as the sole genetic operator. In this paper, we propose two phenotypic mutation techniques and take a step towards advanced phenotypic mutations in Cartesian Genetic…

Neural and Evolutionary Computing · Computer Science 2018-03-19 Roman Kalkreuth

Typefaces are an essential resource employed by graphic designers. The increasing demand for innovative type design work increases the need for good technological means to assist the designer in the creation of a typeface. We present an…

Neural and Evolutionary Computing · Computer Science 2018-06-27 Tiago Martins , João Correia , Ernesto Costa , Penousal Machado

The origin and organizing principles of the genetic code remain fundamental puzzles in life science. The vanishingly low probability of the natural codon-to-amino acid mapping arising by chance has spurred the hypothesis that its structure…

Other Quantitative Biology · Quantitative Biology 2025-10-14 Yudam Seo , Tsvi Tlusty , Junghyo Jo

Evolution of genetic code is studied as the change in the choice of enzymes that are used to synthesize amino acids from the genetic information of nucleic acids. We propose the following theory: the differentiation of physiological states…

Adaptation and Self-Organizing Systems · Physics 2007-05-23 H. Takagi , K. Kaneko , T. Yomo

Human language has a distinct systematic structure, where utterances break into individually meaningful words which are combined to form phrases. We show that natural-language-like systematicity arises in codes that are constrained by a…

Computation and Language · Computer Science 2025-11-19 Richard Futrell , Michael Hahn

Nowadays genetic algorithm (GA) is greatly used in engineering pedagogy as an adaptive technique to learn and solve complex problems and issues. It is a meta-heuristic approach that is used to solve hybrid computation challenges. GA…

Other Computer Science · Computer Science 2020-07-27 Tanweer Alam , Shamimul Qamar , Amit Dixit , Mohamed Benaida

Genetic Algorithms are a popular set of optimization algorithms often used to aid software testing. However, no work has been done to apply systematic software testing techniques to genetic algorithms because of the stochasticity and the…

Software Engineering · Computer Science 2018-08-06 Janette Rounds , Upulee Kanewala

There is growing consensus among neuroscientists that neural circuits critical for survival are the result of genomic decompression processes. We introduce SynaptoGen, a novel computational framework--member of the Connectome Models…

Neural and Evolutionary Computing · Computer Science 2025-09-09 Tommaso Boccato , Matteo Ferrante , Nicola Toschi

Associative learning--forming links between co-occurring items--is fundamental to human cognition, reshaping internal representations in complex ways. Testing hypotheses on how representational changes occur in biological systems is…

Machine Learning · Computer Science 2025-10-27 Camila Kolling , Vy Ai Vo , Mariya Toneva

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

In recent times, the research field of language dynamics has focused on the investigation of language evolution, dividing the work in three evolutive steps, according to the level of complexity: lexicon, categories and grammar. The Naming…

Physics and Society · Physics 2013-07-08 L. Pucci , P. Gravino , V. D. P. Servedio

Cellular automata are discrete and computational models thatcan be shown as general models of complexity. They are used in varied applications to derive the generalized behavior of the presented model. In this paper we have took one such…

Neural and Evolutionary Computing · Computer Science 2020-05-14 Karan Nayak

The talk describes a general approach of a genetic algorithm for multiple objective optimization problems. A particular dominance relation between the individuals of the population is used to define a fitness operator, enabling the genetic…

Artificial Intelligence · Computer Science 2008-09-03 Martin Josef Geiger