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Real-world optimisation problems are often dynamic. Previously good solutions must be updated or replaced due to changes in objectives and constraints. It is often claimed that evolutionary algorithms are particularly suitable for dynamic…

Neural and Evolutionary Computing · Computer Science 2016-07-13 Duc-Cuong Dang , Thomas Jansen , Per Kristian Lehre

Sex is considered as an evolutionary paradox, since its evolutionary advantage does not necessarily overcome the two fold cost of sharing half of one's offspring's genome with another member of the population. Here we demonstrate that…

Populations and Evolution · Quantitative Biology 2015-05-13 Alexander Feigel , Avraham Englander , Assaf Engel

Evolutionary games are a developing sub-field of game theory. This branch of game theory is used in the study of the adaptation of large, but finite, populations of agents to changes in the environment. It assumes that each agent has no…

Computer Science and Game Theory · Computer Science 2023-07-12 E. M. Lorits , E. A. Gubar

Evolution has fascinated quantitative and physical scientists for decades: how can the random process of mutation, recombination, and duplication of genetic information generate the diversity of life? What determines the rate of evolution?…

Populations and Evolution · Quantitative Biology 2018-04-23 Richard A. Neher , Aleksandra M. Walczak

Environmental changes greatly influence the evolution of populations. Here, we study the dynamics of a population of two strains, one growing slightly faster than the other, competing for resources in a time-varying binary environment…

Populations and Evolution · Quantitative Biology 2020-07-28 Ami Taitelbaum , Robert West , Michael Assaf , Mauro Mobilia

Macroevolution is considered as a problem of stochastic dynamics in a system with many competing agents. Evolutionary events (speciations and extinctions) are triggered by fitness records found by random exploration of the agents' fitness…

adap-org · Physics 2017-01-11 Paolo Sibani , Michael Brandt , Preben Alstroem

Evolution is a fundamental process that shapes the biological world we inhabit, and reinforcement learning is a powerful tool used in artificial intelligence to develop intelligent agents that learn from their environment. In recent years,…

Neural and Evolutionary Computing · Computer Science 2023-06-19 Taboubi Ahmed

Recent developments of eco-evolutionary models have shown that evolving feedbacks between behavioral strategies and the environment of game interactions, leading to changes in the underlying payoff matrix, can impact the underlying…

Physics and Society · Physics 2024-06-10 Katherine Betz , Feng Fu , Naoki Masuda

Environmental variability greatly influences the eco-evolutionary dynamics of a population, i.e. it affects how its size and composition evolve. Here, we study a well-mixed population of finite and fluctuating size whose growth is limited…

Populations and Evolution · Quantitative Biology 2021-10-14 Karl Wienand , Erwin Frey , Mauro Mobilia

Evolutionary game theory is an abstract and simple, but very powerful way to model evolutionary dynamics. Even complex biological phenomena can sometimes be abstracted to simple two-player games. But often, the interaction between several…

Populations and Evolution · Quantitative Biology 2011-06-22 Chaitanya S. Gokhale , Arne Traulsen

It is argued that the "generic" evolutionary pathway of advanced technological civilizations are more likely to be optimization-driven than expansion-driven, in contrast to the prevailing opinions and attitudes in both future studies on one…

Astrophysics · Physics 2008-05-14 Milan M. Cirkovic

We revisit in this paper the relation between evolution of species and the mathematical tool of evolutionary games, which has been used to model and predict it. We indicate known shortcoming of this model that restricts the capacity of…

Computer Science and Game Theory · Computer Science 2014-09-29 Ilaria Brunetti , Rachid El-Azouzi , Eitan Altman

Understanding why we age is a long-lived open problem in evolutionary biology. Aging is prejudicial to the individual and evolutionary forces should prevent it, but many species show signs of senescence as individuals age. Here, I will…

Populations and Evolution · Quantitative Biology 2012-01-24 André C. R. Martins

In this paper, we inspect well-known population genetics and social dynamics models. In these models, interacting individuals, while participating in a self-organizing process, give rise to the emergence of complex behaviors and patterns.…

Populations and Evolution · Quantitative Biology 2012-07-11 Sven Banisch , Tanya Araújo

To learn about the past from a sample of genomic sequences, one needs to understand how evolutionary processes shape genetic diversity. Most population genetic inference is based on frameworks assuming adaptive evolution is rare. But if…

Populations and Evolution · Quantitative Biology 2014-03-25 Richard A. Neher

Building ethical machines may involve bestowing upon them the emotional capacity to self-evaluate and repent on their actions. While apologies represent potential strategic interactions, the explicit evolution of guilt as a behavioural…

Multiagent Systems · Computer Science 2025-05-13 Theodor Cimpeanu , Luis Moniz Pereira , The Anh Han

A robotic swarm that is required to operate for long periods in a potentially unknown environment can use both evolution and individual learning methods in order to adapt. However, the role played by the environment in influencing the…

Neural and Evolutionary Computing · Computer Science 2018-04-23 Andreas Steyven , Emma Hart , Ben Paechter

Population structure can be modelled by evolutionary graphs, which can have a substantial, but very subtle influence on the fate of the arising mutants. Individuals are located on the nodes of these graphs, competing with each other to…

Populations and Evolution · Quantitative Biology 2018-10-31 Marius Möller , Laura Hindersin , Arne Traulsen

Genetic algorithms are modeled after the biological evolutionary processes that use natural selection to select the best species to survive. They are heuristics based and low cost to compute. Genetic algorithms use selection, crossover, and…

Neural and Evolutionary Computing · Computer Science 2020-05-28 Mee Seong Im , Venkat R. Dasari

A simulation model of a population having internal (genetic) structure is presented. The population is subject to selection pressure coming from the environment which is the same in the whole system but changes in time. Reproduction has a…

Adaptation and Self-Organizing Systems · Physics 2012-08-31 Andrzej Pekalski , Marcel Ausloos
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