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We present a game of interacting agents which mimics the complex dynamics found in many natural and social systems. These agents modify their strategies periodically, depending on their performances using genetic crossover mechanisms,…

Statistical Mechanics · Physics 2009-11-10 Marko Sysi-Aho , Anirban Chakraborti , Kimmo Kaski

We propose a variation of the standard genetic algorithm that incorporates social interaction between the individuals in the population. Our goal is to understand the evolutionary role of social systems and its possible application as a…

Neural and Evolutionary Computing · Computer Science 2010-07-05 Rafeal Lahoz-Beltra , Gabriela Ochoa , Uwe Aickelin

The practice of evolutionary algorithms involves the tuning of many parameters. How big should the population be? How many generations should the algorithm run? What is the (tournament selection) tournament size? What probabilities should…

Neural and Evolutionary Computing · Computer Science 2018-06-08 Moshe Sipper , Weixuan Fu , Karuna Ahuja , Jason H. Moore

This paper explores adaptive problem solving with a game designed to support the development of problem-solving skills. Using an adaptive, AI-powered puzzle game, our adaptive problem-solving system dynamically generates pathfinding-based…

Artificial Intelligence · Computer Science 2025-12-09 Matthew McConnell , Richard Zhao

The design and the implementation of a genetic algorithm are described. The applicability domain is on structure-activity relationships expressed as multiple linear regressions and predictor variables are from families of structure-based…

Neural and Evolutionary Computing · Computer Science 2009-06-29 Lorentz Jantschi

In the very large debates on ethics of algorithms, this paper proposes an analysis on human responsibility. On one hand, algorithms are designed by some humans, who bear a part of responsibility in the results and unexpected impacts.…

Computers and Society · Computer Science 2024-07-15 Odile Bellenguez , Nadia Brauner , Alexis Tsoukiàs

Genetic algorithms are considered as one of the most efficient search techniques. Although they do not offer an optimal solution, their ability to reach a suitable solution in considerably short time gives them their respectable role in…

Neural and Evolutionary Computing · Computer Science 2014-01-22 Ayman M. Bahaa-Eldin , A. M. A. Wahdan , H. M. K. Mahdi

The rapidly increasing interest in the quantum properties of living matter stimulates a discussion of the fundamental properties of life as well as quantum mechanics. In this discussion often concepts are used that originate in philosophy…

History and Philosophy of Physics · Physics 2016-07-27 Alfred Driessen

The search for life outside the Solar System is an endeavour of astronomers all around the world. With hundreds of exoplanets being discovered due to advances in astronomy, there is a need to classify the habitability of these exoplanets.…

Neural and Evolutionary Computing · Computer Science 2021-01-19 Sriram Krishna , Niharika Pentapati

Machine learning algorithms are now frequently used in sensitive contexts that substantially affect the course of human lives, such as credit lending or criminal justice. This is driven by the idea that `objective' machines base their…

Machine Learning · Computer Science 2019-01-17 Songül Tolan

In computer interfaces in general, especially in information retrieval tasks, it is important to be able to quickly find and retrieve information. State of the art approach, used, for example, in search engines, is not effective as it…

Information Retrieval · Computer Science 2015-02-20 Dmytro Filatov , Taras Filatov

Many real-world optimization problems occur in environments that change dynamically or involve stochastic components. Evolutionary algorithms and other bio-inspired algorithms have been widely applied to dynamic and stochastic problems.…

Neural and Evolutionary Computing · Computer Science 2020-01-30 Vahid Roostapour , Mojgan Pourhassan , Frank Neumann

Evolutionary multitasking has recently emerged as a novel paradigm that enables the similarities and/or latent complementarities (if present) between distinct optimization tasks to be exploited in an autonomous manner simply by solving them…

Neural and Evolutionary Computing · Computer Science 2016-07-20 Abhishek Gupta , Yew-Soon Ong

This article presents results of experimental studies the effectiveness of the genetic algorithm that was applied to effective queries creation and relevant document selection. Studies were carried out to the comparative analysis of the…

Information Retrieval · Computer Science 2015-04-06 V. K. Ivanov , B. V. Palyukh

Genetic Algorithms (GA) are a class of metaheuristic global optimization methods inspired by the process of natural selection among individuals in a population. Despite their widespread use, a comprehensive theoretical analysis of these…

Optimization and Control · Mathematics 2025-02-24 Giacomo Borghi , Lorenzo Pareschi

Artificial life is a research field studying what processes and properties define life, based on a multidisciplinary approach spanning the physical, natural and computational sciences. Artificial life aims to foster a comprehensive study of…

Artificial Intelligence · Computer Science 2023-08-02 Manuel Baltieri , Hiroyuki Iizuka , Olaf Witkowski , Lana Sinapayen , Keisuke Suzuki

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

The pursuit of creating artificial intelligence (AI) mirrors our longstanding fascination with understanding our own intelligence. From the myths of Talos to Aristotelian logic and Heron's inventions, we have sought to replicate the marvels…

Neurons and Cognition · Quantitative Biology 2024-11-26 Nima Dehghani , Michael Levin

Here we propose an evolutionary algorithm that self modifies its operators at the same time that candidate solutions are evolved. This tackles convergence and lack of diversity issues, leading to better solutions. Operators are represented…

Neural and Evolutionary Computing · Computer Science 2017-12-19 Andres Felipe Cruz Salinas , Jonatan Gomez Perdomo

Artificial life aims to understand the fundamental principles of biological life by creating computational models that exhibit life-like properties. Although artificial life systems show promise for simulating biological evolution,…

Neural and Evolutionary Computing · Computer Science 2025-06-04 Niko Lorantos , Lee Spector