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Simulated Evolution and Learning

Overview of attention for book
Simulated Evolution and Learning
Springer, Cham

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Solving Dynamic Optimisation Problem with Variable Dimensions
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    Chapter 2 A Probabilistic Evolutionary Optimization Approach to Compute Quasiparticle Braids
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    Chapter 3 Adaptive System Design by a Simultaneous Evolution of Morphology and Information Processing
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    Chapter 4 Generating Software Test Data by Particle Swarm Optimization
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    Chapter 5 A Steady-State Genetic Algorithm for the Dominating Tree Problem
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    Chapter 6 Evolution of Developmental Timing for Solving Hierarchically Dependent Deceptive Problems
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    Chapter 7 The Introduction of Asymmetry on Traditional 2-Parent Crossover Operators for Crowding and Its Effects
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    Chapter 8 The Performance Effects of Interaction Frequency in Parallel Cooperative Coevolution
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    Chapter 9 Customized Selection in Estimation of Distribution Algorithms
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    Chapter 10 A Hybrid GP-Tabu Approach to QoS-Aware Data Intensive Web Service Composition
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    Chapter 11 A Modified Screening Estimation of Distribution Algorithm for Large-Scale Continuous Optimization
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    Chapter 12 Clustering Problems for More Useful Benchmarking of Optimization Algorithms
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    Chapter 13 An Analysis of Differential Evolution Parameters on Rotated Bi-objective Optimization Functions
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    Chapter 14 Fuzzy Clustering with Fitness Predator Optimizer for Multivariate Data Problems
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    Chapter 15 Effects of Mutation and Crossover Operators in the Optimization of Traffic Signal Parameters
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    Chapter 16 A GP Approach to QoS-Aware Web Service Composition and Selection
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    Chapter 17 A Novel Hybrid Multi-objective Optimization Framework: Rotating the Objective Space
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    Chapter 18 PaCcET: An Objective Space Transformation to Iteratively Convexify the Pareto Front
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    Chapter 19 Evolving Hard and Easy Traveling Salesman Problem Instances: A Multi-objective Approach
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    Chapter 20 Simulated Evolution and Learning
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    Chapter 21 Extending AεSεH from Many-objective to Multi-objective Optimization
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    Chapter 22 User Preferences for Approximation-Guided Multi-objective Evolution
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    Chapter 23 Multi-objective Optimisation, Software Effort Estimation and Linear Models
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    Chapter 24 Adaptive Update Range of Solutions in MOEA/D for Multi and Many-Objective Optimization
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    Chapter 25 Classification of Lumbar Ultrasound Images with Machine Learning
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    Chapter 26 Schemata Bandits for Binary Encoded Combinatorial Optimisation Problems
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    Chapter 27 Anomaly Detection Using Replicator Neural Networks Trained on Examples of One Class
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    Chapter 28 Walking Motion Learning of Quadrupedal Walking Robot by Profit Sharing That Can Learn Deterministic Policy for POMDPs Environments
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    Chapter 29 Genetic Programming for Multiclass Texture Classification Using a Small Number of Instances
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    Chapter 30 A Stepwise Multi-centroid Classification Learning Algorithm with GPU Implementation
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    Chapter 31 Dynamic Selection of Evolutionary Algorithm Operators Based on Online Learning and Fitness Landscape Metrics
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    Chapter 32 Learning Patterns of States in Time Series by Genetic Programming
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    Chapter 33 Reusing Learned Functionality to Address Complex Boolean Functions
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    Chapter 34 Analysis of Online Signature Based Learning Classifier Systems for Noisy Environments: A Feedback Control Theoretic Approach
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    Chapter 35 Multi-objective Multiagent Credit Assignment Through Difference Rewards in Reinforcement Learning
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    Chapter 36 On the Impact of Utility Functions in Interactive Evolutionary Multi-objective Optimization
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    Chapter 37 Beyond the Edge of Feasibility: Analysis of Bottlenecks
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    Chapter 38 Adaptive Risk Aversion in Social Dilemmas
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    Chapter 39 Fitness Landscape Analysis of Circles in a Square Packing Problems
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    Chapter 40 Local Landscape Patterns for Fitness Landscape Analysis
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    Chapter 41 Why Advanced Population Initialization Techniques Perform Poorly in High Dimension?
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    Chapter 42 Bloat and Generalisation in Symbolic Regression
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    Chapter 43 Improved PSO for Feature Selection on High-Dimensional Datasets
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    Chapter 44 Multi-objective Feature Selection in Classification: A Differential Evolution Approach
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    Chapter 45 A Multi-objective Optimization Method for Product Feature Fatigue Problem
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    Chapter 46 Genetic Programming for Channel Selection from Multi-stream Sensor Data with Application on Learning Risky Driving Behaviours
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    Chapter 47 Variable Neighbourhood Iterated Improvement Search Algorithm for Attribute Reduction Problems
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    Chapter 48 PSO and Statistical Clustering for Feature Selection: A New Representation
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    Chapter 49 Feature Selection Method with Proportionate Fitness Based Binary Particle Swarm Optimization
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    Chapter 50 Genetic Programming for Measuring Peptide Detectability
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    Chapter 51 Overview of Particle Swarm Optimisation for Feature Selection in Classification
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    Chapter 52 A Comparison between Two Evolutionary Hyper-Heuristics for Combinatorial Optimisation
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    Chapter 53 Simulated Evolution and Learning
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    Chapter 54 Load Balance Aware Genetic Algorithm for Task Scheduling in Cloud Computing
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    Chapter 55 Selection Schemes in Surrogate-Assisted Genetic Programming for Job Shop Scheduling
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    Chapter 56 Developing a Hyper-Heuristic Using Grammatical Evolution and the Capacitated Vehicle Routing Problem
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    Chapter 57 An Organizational Cooperative Coevolutionary Algorithm for Multimode Resource-Constrained Project Scheduling Problems
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    Chapter 58 Scaling Up Solutions to Storage Location Assignment Problems by Genetic Programming
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    Chapter 59 Dual Population Genetic Algorithm for the Cardinality Constrained Portfolio Selection Problem
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    Chapter 60 An Evolutionary Algorithm for TD-LTE Resource Allocation Based on Adaptive Fairness Threshold
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    Chapter 61 Enhancing Heuristics for Order Acceptance and Scheduling Using Genetic Programming
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    Chapter 62 Application of Adaptive Streaming Technology in Remotely Driven Electric Vehicles
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    Chapter 63 Optimising Wi-Fi Installations Using a Multi-Objective Evolutionary Algorithm
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    Chapter 64 Automated Design of Architectural Layouts Using a Multi-Objective Evolutionary Algorithm
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    Chapter 65 An Approach for Real-Time Frame Size Adaptation in M-JPEG Streams
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    Chapter 66 Automatic Melody Generation Considering User’s Evaluation Using Interactive Genetic Algorithm
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    Chapter 67 Object Recognition by Stochastic Metric Learning
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    Chapter 68 Automatic Resolution Selection for Edge Detection Using Genetic Programming
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    Chapter 69 Evolutionary Feature Combination Based Seed Learning for Diffusion-Based Saliency
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    Chapter 70 Analysis of Hybrid Classification Approach to Differentiate Dense and Non-dense Grass Regions
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    Chapter 71 Image Segmentation: A Survey of Methods Based on Evolutionary Computation
Overall attention for this book and its chapters
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About this Attention Score

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  • Average Attention Score compared to outputs of the same age and source

Mentioned by

2 tweeters


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21 Mendeley
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Simulated Evolution and Learning
Published by
Lecture notes in computer science, January 2014
DOI 10.1007/978-3-319-13563-2
978-3-31-913562-5, 978-3-31-913563-2

Grant Dick, Will N. Browne, Peter Whigham, Mengjie Zhang, Lam Thu Bui, Hisao Ishibuchi, Yaochu Jin, Xiaodong Li, Yuhui Shi, Pramod Singh, Kay Chen Tan, Ke Tang


Grant Dick, Will N. Browne, Peter Whigham, Mengjie Zhang, Lam Thu Bui, Hisao Ishibuchi, Yaochu Jin, Xiaodong Li, Yuhui Shi, Pramod Singh, Kay Chen Tan, Ke Tang

Twitter Demographics

The data shown below were collected from the profiles of 2 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 21 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 5%
Unknown 20 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 3 14%
Student > Postgraduate 2 10%
Student > Master 1 5%
Lecturer > Senior Lecturer 1 5%
Researcher 1 5%
Other 1 5%
Unknown 12 57%
Readers by discipline Count As %
Computer Science 4 19%
Philosophy 1 5%
Biochemistry, Genetics and Molecular Biology 1 5%
Agricultural and Biological Sciences 1 5%
Social Sciences 1 5%
Other 1 5%
Unknown 12 57%

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 03 October 2014.
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Altmetric has tracked 14,563,402 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,468 research outputs from this source. They receive a mean Attention Score of 4.5. This one is in the 45th percentile – i.e., 45% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 262,730 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 44th percentile – i.e., 44% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 78 others from the same source and published within six weeks on either side of this one. This one is in the 46th percentile – i.e., 46% of its contemporaries scored the same or lower than it.