Evolution, Complexity and Artificial Life

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 dir...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Άλλοι συγγραφείς: Cagnoni, Stefano (Επιμελητής έκδοσης), Mirolli, Marco (Επιμελητής έκδοσης), Villani, Marco (Επιμελητής έκδοσης)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2014.
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
Πίνακας περιεχομένων:
  • 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.