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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

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

This document is the Special Issue of the First International Conference on the Evolution and Development of the Universe (EDU 2008). Please refer to the preface and introduction for more details on the contributions. Keywords:…

Two major goals in machine learning are the discovery and improvement of solutions to complex problems. In this paper, we argue that complexification, i.e. the incremental elaboration of solutions through adding new structure, achieves both…

Artificial Intelligence · Computer Science 2011-07-04 R. Miikkulainen , K. O. Stanley

The rise of multicellularity in the early evolution of life represents a major challenge for evolutionary biology. Guidance for finding answers has emerged from disparate fields, from phylogenetics to modelling and synthetic biology, but…

Populations and Evolution · Quantitative Biology 2015-11-09 Salva Duran-Nebreda , Adriano Bonforti , Raul Montañez , Sergi Valverde , Ricard Solé

A celebrated and controversial hypothesis conjectures that some biological systems --parts, aspects, or groups of them-- may extract important functional benefits from operating at the edge of instability, halfway between order and…

Statistical Mechanics · Physics 2018-08-01 Miguel A. Munoz

Understanding the origins of complexity is a fundamental challenge with implications for biological and technological systems. Network theory emerges as a powerful tool to model complex systems. Networks are an intuitive framework to…

Disordered Systems and Neural Networks · Physics 2024-10-22 Blai Vidiella , Salva Duran-Nebreda , Sergi Valverde

We study open-ended evolution by focusing on computational and information-processing dynamics underlying major evolutionary transitions. In doing so, we consider biological organisms as hierarchical dynamical systems that generate…

Over the past 30 years many researchers in the field of evolutionary computation have put a lot of effort to introduce various approaches for solving hard problems. Most of these problems have been inspired by major industries so that…

Neural and Evolutionary Computing · Computer Science 2016-06-23 Mohammad Reza Bonyadi , Zbigniew Michalewicz , Frank Neumann , Markus Wagner

Complex evolving systems such as the biosphere, ecosystems and societies exhibit sudden collapses, for reasons that are only partially understood. Here we study this phenomenon using a mathematical model of a system that evolves under…

Adaptation and Self-Organizing Systems · Physics 2007-05-23 Ravi Mehrotra , Vikram Soni , Sanjay Jain

We will review some of the theoretical progresses that have been in the study of complex systems in physics and of their applications to biology.

Condensed Matter · Physics 2008-02-03 Giorgio Parisi

Evolutionary algorithm research and applications began over 50 years ago. Like other artificial intelligence techniques, evolutionary algorithms will likely see increased use and development due to the increased availability of computation,…

Neural and Evolutionary Computing · Computer Science 2019-06-24 Andrew N. Sloss , Steven Gustafson

The emergence of multicellularity and developmental programs are among the major problems of evolutionary biology. Traditionally, research in this area has been based on the combination of data analysis and experimental work on one hand and…

Populations and Evolution · Quantitative Biology 2014-03-14 Ricard V. Solé , Salva Duran-Nebreda

In this paper we propose an approach for measuring growth of complexity of emerging patterns in complex systems such as cellular automata. We discuss several ways how a metric for measuring the complexity growth can be defined. This…

Cellular Automata and Lattice Gases · Physics 2022-07-22 Hugo Cisneros , Josef Sivic , Tomas Mikolov

In biology, the evolution of increasingly cooperative groups has shaped the history of life. Genes collaborate in the control of cells; cells efficiently divide tasks to produce cohesive multicellular individuals; individual members of…

Populations and Evolution · Quantitative Biology 2011-12-15 Steven A. Frank

Life systems are complex and hierarchical, with diverse components at different scales, yet they sustain themselves, grow, and evolve over time. How can a theory of such complex biological states be developed? Here we note that for a…

Biological Physics · Physics 2024-10-03 Kunihiko Kaneko

This text introduces the twin deadlocks of strong artificial life. Conceptualization of life is a deadlock both because of the existence of a continuum between the inert and the living, and because we only know one instance of life.…

Artificial Intelligence · Computer Science 2007-05-23 J. -Ph Rennard

Bedau has developed a general set of evolutionary statistics that quantify the adaptive component of evolutionary processes. On the basis of these measures, he has proposed a set of 4 classes of evolutionary system. All artificial life…

Adaptation and Self-Organizing Systems · Physics 2009-09-29 Russell K. Standish

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

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
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