Simulated Evolution and Learning
Springer International Publishing (Verlag)
978-3-319-68758-2 (ISBN)
The 85 papers presented in this volume were carefully reviewed and selected from 145 submissions. They were organized in topical sections named: evolutionary optimisation; evolutionary multiobjective optimisation; evolutionary machine learning; theoretical developments; feature selection and dimensionality reduction; dynamic and uncertain environments; real-world applications; adaptive systems; and swarm intelligence.
Evolutionary Optimisation.- Maximum Likelihood Estimation based on Random Subspace EDA: Application to Extrasolar Planet Detection.- Evolutionary Games Network Reconstruction by Memetic Algorithm with l1/2 Regularization.- A Simple Brain Storm Optimization Algorithm via Visualizing Confidence Intervals.- Simulated Annealing with a Time-slot Heuristic for Ready-mix Concrete Delivery.- A Sequential Learnable Evolutionary Algorithm with a Novel Knowledge Base Generation Method.- Using Parallel Strategies to Speed Up Pareto Local Search.- Differential evolution based hyper-heuristic for the flexible job-shop scheduling problem with fuzzy processing time.- ACO-iRBA: A Hybrid Approach to TSPN with Overlapping Neighborhoods.- An Evolutionary Algorithm with A New Coding Scheme for Multi-objective Portfolio Optimization.- Exact Approaches for the Travelling Thief Problem.- On the Use of Dynamic Reference Points in HypE.- Multi-Factorial Evolutionary Algorithm Based on M2M Decomposition.- An Efficient Local Search Algorithm for Minimum Weighted Vertex Cover on Massive Graphs.- Interactive Genetic Algorithm with Group Intelligence Articulated Possibilistic Condition Preference Model.- GP-Based Approach to Comprehensive Quality-Aware Automated Semantic Web Service Composition.- Matrix Factorization based Benchmark Set Analysis: A Case Study on HyFlex.-Learning to Describe Collective Search Behavior of Evolutionary Algorithms in Solution Space.- Evolutionary Multiobjective Optimisation.- A Hierarchical Decomposition-based Evolutionary Many-objective Algorithm.- Adjusting Parallel Coordinates for Investigating Multi-Objective Search.- An Elite Archive-based MOEA/D Algorithm.- A constraint partitioning method based on minimax strategy for constrained multiobjective optimization problems.- A Fast Objective Reduction Algorithm based on Dominance Structure for Many Objective Optimization.- A memetic algorithm based on decomposition and extended search for Multi-Objective CapacitatedArc Routing Problem.- Improvement of reference points for decomposition based multi-objective evolutionary algorithms.- Multi-Objective Evolutionary Optimization for Autonomous Intersection Management.- Study of an adaptive control of aggregate functions in MOEA/D.- Use of Inverted Triangular Weight Vectors in Decomposition-Based Many-Objective Algorithms.- Surrogate Model Assisted Multi-Objective Differential Evolution Algorithm for Performance Optimization at Software Architecture Level.- Normalized Ranking Based Particle Swarm Optimizer for Many Objective Optimization.- Evolutionary Machine Learning.- A Study on Pre-Training Deep Neural Networks Using Particle Swarm Optimisation.- Simple Linkage Identification Using Genetic Clustering.- Learning of Sparse Fuzzy Cognitive Maps Using Evolutionary Algorithm with Lasso Initialization.- A Bayesian Restarting Approach to Algorithm Selection.- Evolutionary Learning based Iterated Local Search for Google Machine Reassignment Problems.- Geometric Semantic Genetic Programming with Perpendicular Crossover and Random Segment Mutation for Symbolic Regression.- Constrained Dimensionally Aware Genetic Programming for Evolving Interpretable Dispatching Rules in Dynamic Job Shop Scheduling.- Visualisation and Optimisation of Learning Classifier Systems for Multiple Domain Learning.- Adaptive Memetic Algorithm Based Evolutionary Multi-tasking Single-objective Optimization.- Effective Policy Gradient Search for Reinforcement Learning through NEAT based Feature Extraction.- Generalized Hybrid Evolutionary Algorithm Framework with a Mutation Operator Requiring no Adaptation.- A Multitree Genetic Programming Representation for Automatically Evolving Texture Image Descriptors.- Theoretical Developments.- Running-time Analysis of Particle Swarm Optimization with a Single Particle Based on Average Gain.- Evolutionary Computation Theory for Remote Sensing Image Clustering: A Survey.- Feature Selection and Dimensionality Reduction.- New Rep
| Erscheinungsdatum | 18.11.2017 |
|---|---|
| Reihe/Serie | Lecture Notes in Computer Science | Theoretical Computer Science and General Issues |
| Zusatzinfo | XXII, 1041 p. 317 illus. |
| Verlagsort | Cham |
| Sprache | englisch |
| Maße | 155 x 235 mm |
| Gewicht | 1573 g |
| Themenwelt | Mathematik / Informatik ► Informatik ► Netzwerke |
| Informatik ► Software Entwicklung ► User Interfaces (HCI) | |
| Informatik ► Theorie / Studium ► Algorithmen | |
| Schlagworte | Algorithm Analysis • Algorithm analysis and problem complexity • Algorithm design • Applications • Artificial Intelligence • computation by abstract devices • Computer Science • Computing Methodologies • conference proceedings • evolutionary algorithms • evolutionary computation • evolutionary learning • evolutionary optimization • Genetic algorithms • genetic programming • Informatics • Informatik • machine learning • Modeling and Simulation • Multiobjective Optimization • Pareto principle • Particle swarm optimization • Research • search technologies • user interface design & usability • User interface design & usability |
| ISBN-10 | 3-319-68758-1 / 3319687581 |
| ISBN-13 | 978-3-319-68758-2 / 9783319687582 |
| Zustand | Neuware |
| Informationen gemäß Produktsicherheitsverordnung (GPSR) | |
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