Evolution, complexity and artificial life [electronic resource] / Stefano Cagnoni, Marco Mirolli, Marco Villani, editors.
Cagnoni, Stefano, 1961- editor of compilation.; Mirolli, Marco, editor of compilation.; Villani, Marco, editor of compilation.
2014
Q325
Available Online

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Title Evolution, complexity and artificial life [electronic resource] / Stefano Cagnoni, Marco Mirolli, Marco Villani, editors.
ISBN 9783642375774 electronic book
3642375774 electronic book
9783642375767
DOI https://doi.org/10.1007/978-3-642-37577-4
Published Heidelberg : Springer, 2014.
Language English
Description 1 online resource.
Other Standard Identifiers 10.1007/978-3-642-37577-4 doi
Call Number Q325
Dewey Decimal Classification 006.3
Summary Traditionally, artificial evolution, complex systems, and artificial life were separate fields, with their own research communities, but we are now seeing increased engagement and hybridization. Evolution and complexity characterize biological life but they also permeate artificial life, through direct modeling of biological processes and the creation of populations of interacting entities from which complex behaviors can emerge and evolve. This latter consideration also indicates the breadth of the related topics of interest, and of the different study viewpoints, ranging from purely scientific and exploratory approaches aimed at verifying biological theories to technology-focused applied research aimed at solving difficult real-world problems. This edited book is structured into sections on research issues, biological modeling, mind and society, applications, and evolution. The contributing authors are among the leading scientists in these fields, and their chapters describe interesting ideas and results in topics such as artefacts, evolutionary dynamics, gene regulatory networks, biological modeling, cell differentiation, chemical communication, cumulative learning, embodied agents, cultural evolution, an a-life approach to games, nanoscale search by molecular spiders, using genetic programming for disease survival prediction, a neuroevolutionary approach to electrocardiography, trust-adaptive grid computing, detecting cheating bots in online games, distribution search in evolutionary multiobjective optimization, and differential evolution implemented on multicore CPUs. The book will be of interest to researchers in the fields of artificial intelligence, artificial life, and computational intelligence.
Bibliography, etc. Note Includes bibliographical references.
Access Note Access limited to authorized users.
Source of Description Description based on print version record.
Added Author Cagnoni, Stefano, 1961- editor of compilation.
Mirolli, Marco, editor of compilation.
Villani, Marco, editor of compilation.
Available in Other Form Evolution, complexity and artificial life
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One Artefact: Many Phenomena
Taming the Complexity of Natural and Artificial Evolutionary Dynamics
Models of Gene Regulation: Integrating Modern Knowledge into the Random Boolean Network Framework
Attractors Perturbations in Biological Modelling: Avalanches and Cellular Differentiation
Automatic Design of Boolean Networks for Modeling Cell Differentiation
Towards the Engineering of Chemical Communication Between Semi-synthetic and Natural Cells
Cumulative Learning Through Intrinsic Reinforcements
Development of Categorization Abilities in Evolving Embodied Agents: A Study of Internal Representations with External Social Inputs
Regulatory Traits: Cultural Influences on Cultural Evolution
Building up Serious Games with an Artificial Life Approach: Two Case Studies
The Effects of Multivalency and Kinetics in Nanoscale Search by Molecular Spiders
Towards the Use of Genetic Programming for the Prediction of Survival in Cancer
A Neuro-evolutionary Approach to Electrocardiographic Signal Classification
Self-organisation and Evolution for Trust-Adaptive Grid Computing Agents
Honest vs. Cheating Bots in PATROL-Based Real-Time Strategy MMOGs
Distribution Search on Evolutionary Many-Objective Optimization: Selection Mappings and Recombination Rate
Concurrent Implementation Techniques Using Differential Evolution for Multi-core CPUs: A Comparative Study Using Statistical Tests.

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