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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

We consider adaptive decision-making problems where an agent optimizes a cumulative performance objective by repeatedly choosing among a finite set of options. Compared to the classical prediction-with-expert-advice set-up, we consider…

Machine Learning · Computer Science 2023-04-10 Michael Muehlebach

Empirical evidence shows that human behaviour often deviates from game-theoretical rationality. For instance, humans may hold unrealistic expectations about future outcomes. As the evolutionary roots of such biases remain unclear, we…

Multiagent Systems · Computer Science 2025-08-29 Marco Saponara , Elias Fernandez Domingos , Jorge M. Pacheco , Tom Lenaerts

The process of evolutionary emergence of purposeful adaptive behavior is investigated by means of computer simulations. The model proposed implies that there is an evolving population of simple agents, which have two natural needs: energy…

Neural and Evolutionary Computing · Computer Science 2007-05-23 Mikhail S. Burtsev , Vladimir G. Redko , Roman V. Gusarev

One of the defining features of living systems is their adaptability to changing environmental conditions. This requires organisms to extract temporal and spatial features of their environment, and use that information to compute the…

Neurons and Cognition · Quantitative Biology 2024-02-27 Maria Sol Vidal-Saez , Oscar Vilarroya , Jordi Garcia-Ojalvo

Animals behave adaptively in the environment with multiply competing goals. Understanding of the mechanisms underlying such goal-directed behavior remains a challenge for neuroscience as well for adaptive system research. To address this…

Neural and Evolutionary Computing · Computer Science 2012-04-17 Konstantin Lakhman , Mikhail Burtsev

The last few years have witnessed substantial progress in the field of embodied AI where artificial agents, mirroring biological counterparts, are now able to learn from interaction to accomplish complex tasks. Despite this success,…

Computer Vision and Pattern Recognition · Computer Science 2022-01-04 Sarah Pratt , Luca Weihs , Ali Farhadi

Most decision tree induction algorithms are based on a greedy top-down recursive partitioning strategy for tree growth. In this paper, we propose several methods for induction of decision trees and their ensembles based on evolutionary…

Neural and Evolutionary Computing · Computer Science 2020-02-04 Evgeny Dolotov , Nikolai Zolotykh

One strategy for winning a coevolutionary struggle is to evolve rapidly. Most of the literature on host-pathogen coevolution focuses on this phenomenon, and looks for consequent evidence of coevolutionary arms races. An alternative…

Populations and Evolution · Quantitative Biology 2014-12-17 Erick Chastain , Rustom Antia , Carl T. Bergstrom

It has been proposed that, since the origin of life and the ensuing evolution of biological species, a second evolutionary process has appeared on our planet. It is the evolution of culture-e.g., ideas, beliefs, and artifacts. Does culture…

Populations and Evolution · Quantitative Biology 2019-07-09 Liane Gabora , Diederik Aerts

We describe the results of analytic calculations and computer simulations of adaptive predictors (predictive agents) responding to an evolving chaotic environment and to one another. Our simulations are designed to quantify adaptation and…

adap-org · Physics 2008-02-03 Alfred Hübler , David Pines

Simulation of population dynamics is a central research theme in computational biology, which contributes to understanding the interactions between predators and preys. Conventional mathematical tools of this theme, however, are incapable…

Multiagent Systems · Computer Science 2020-02-11 Jun Yamada , John Shawe-Taylor , Zafeirios Fountas

Animals often demonstrate a remarkable ability to adapt to their environments during their lifetime. They do so partly due to the evolution of morphological and neural structures. These structures capture features of environments shared…

Machine Learning · Computer Science 2024-01-30 Corentin Léger , Gautier Hamon , Eleni Nisioti , Xavier Hinaut , Clément Moulin-Frier

The learning dynamics of biological brains and artificial neural networks are of interest to both neuroscience and machine learning. A key difference between them is that neural networks are often trained from a randomly initialized state…

Neural and Evolutionary Computing · Computer Science 2025-05-19 Benjamin Midler , Alejandro Pan Vazquez

Evolution and learning are two of the fundamental mechanisms by which life adapts in order to survive and to transcend limitations. These biological phenomena inspired successful computational methods such as evolutionary algorithms and…

Neural and Evolutionary Computing · Computer Science 2019-05-10 Jan Schuchardt , Vladimir Golkov , Daniel Cremers

Animal vision is thought to optimize various objectives from metabolic efficiency to discrimination performance, yet its ultimate objective is to facilitate the survival of the animal within its ecological niche. However, modeling animal…

Neural and Evolutionary Computing · Computer Science 2024-02-09 Sacha Sokoloski , Jure Majnik , Philipp Berens

Biological populations are subject to fluctuating environmental conditions. Different adaptive strategies can allow them to cope with these fluctuations: specialization to one particular environmental condition, adoption of a generalist…

Populations and Evolution · Quantitative Biology 2017-09-27 Andreas Mayer , Thierry Mora , Olivier Rivoire , Aleksandra M. Walczak

Information is a key concept in evolutionary biology. Information is stored in biological organism's genomes, and used to generate the organism as well as to maintain and control it. Information is also "that which evolves". When a…

Populations and Evolution · Quantitative Biology 2012-07-25 Christoph Adami

Darwinian evolution of the biological brain is documented through multiple lines of evidence, although the modes of evolutionary changes remain unclear. Drawing inspiration from the evolved neural systems (e.g., visual cortex), deep…

Neural and Evolutionary Computing · Computer Science 2024-08-13 Guodong Du , Runhua Jiang , Senqiao Yang , Haoyang Li , Wei Chen , Keren Li , Sim Kuan Goh , Ho-Kin Tang

We demonstrate how an evolutionary algorithm can be extended with a curriculum learning process that selects automatically the environmental conditions in which the evolving agents are evaluated. The environmental conditions are selected so…

Neural and Evolutionary Computing · Computer Science 2021-02-18 Nicola Milano , Stefano Nolfi