Artificial Life and Evolutionary Computation

Table of Contents

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   Book Overview
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   Chapter 1 Energy Consumption of Evolutionary Algorithms in JavaScript
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   Chapter 2 A Tabu Search Algorithm for the Map Labeling Problem
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   Chapter 3 How to Turn a Leaky Learner into a Sealed One
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   Chapter 4 Capturing Emerging Complexity in Lenia
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   Chapter 5 On the Detection of Significant Pairwise Interactions in Complex Systems
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   Chapter 6 The Properties of Pseudo-Attractors in Random Boolean Networks
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   Chapter 7 Analysing the Expressiveness of Metabolic Networks Representations
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   Chapter 8 scFBApy: A Python Framework for Super-Network Flux Balance Analysis
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    Chapter 9 Semantic Information as a Measure of Synthetic Cells’ Knowledge of the Environment
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    Chapter 10 General Lines, Routes and Perspectives of Wetware Embodied AI. From Its Organizational Bases to a Glimpse on Social Chemical Robotics
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    Chapter 11 A Proposed Mechanism for  in vivo Programming Transmembrane Receptors
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    Chapter 12 Kauffman Model with Spatially Separated Ligation and Cleavage Reactions
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    Chapter 13 Percolation Breakdown in Binary and Ternary Monodisperse and Polydisperse Systems of Spherical Particles
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    Chapter 14 Entangled Gondolas. Design of Multi-layer Networks of Quantum-Driven Robotic Swarms
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    Chapter 15 Generalizations of Evolved Decision-Making Mechanisms in Swarm Collective Perception
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    Chapter 16 An Investigation of Graceful Degradation in Boolean Network Robots Subject to Online Adaptation
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    Chapter 17 Blockchain-Empowered PSO for Scalable Swarm Robotics
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    Chapter 18 Hybrid GP/PSO Representation of 1-D Signals in an Autoencoder Fashion
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    Chapter 19 Local Delay Plasticity Supports Generalized Learning in Spiking Neural Networks
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    Chapter 20 Improving PVC Detection in ECG Signals: A Recurrent Neural Network Approach
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    Chapter 21 Clustering Trajectories to Study Diabetic Kidney Disease
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    Chapter 22 Multi-classification of Alzheimer’s Disease by NSGA-II Slices Optimization and Fusion Deep Learning
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    Chapter 23 Exploiting the Potential of Bayesian Networks in Deriving New Insight into Diabetic Kidney Disease (DKD)
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    Chapter 24 A Genetic Algorithm for Feature Selection for Alzheimer’s Disease Detection Using a Deep Transfer Learning Approach
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    Chapter 25 Learning Whether to be Informed in an Agent-Based Evolutionary Market Model
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    Chapter 26 Heterogeneous Mean-Field Analysis of Best-of-n Decision Making in Networks with Zealots
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    Chapter 27 Does ‘Community Detection’ Find Real Emerging Meso-structures? A Statistical Test Based on Complex Networks Methods
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    Chapter 28 Self-loops in Social Networks: Behavior of Eigenvector Centrality
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    Chapter 29 Evolutionary Story Sifting over the Log of a Social Simulation
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    Chapter 30 Evolution of Attraction for Cooperation