Artificial Life and Computational Intelligence
Springer International Publishing (Verlag)
978-3-319-28269-5 (ISBN)
This bookconstitutes the proceedings of the Second Australasian Conference on ArtificialLife and Computational Intelligence, ACALCI 2016, held in Canberra, ACT,Australia, in February 2016.
The 30 fullpapers presented in this volume were carefully reviewed and selected from 41submissions. They are organized in topical sections named: mathematicalmodeling and theory; learning and optimization; planning and scheduling;feature selection; and applications and games.
Mathematical Modeling and Theory.- FractalDimension - A Spatial and Visual Design Technique for the Creation of LifelikeArtificial Forms.- Using Closed Sets to Model Cognitive Behavior.- Learning andOptimization.- Solving dynamic optimisation problem with known changeableboundaries.- Compaction for Code Fragment Based Learning Classifier Systems.- TheBoon of Gene-Culture Interaction for Effective Evolutionary Multitasking.- AStudy on Performance Metrics to Identify Solutions of Interest From a Trade-offSet.- Dynamic Configuration of Differential Evolution Control Parameters andOperators.- Exploring the Feasible Space using Constraint Consensus in Solving ConstrainedOptimization Problems.- A Nested Differential Evolution based Algorithm forSolving Multi-objective Bilevel Optimization Problems.- Parkinson's DiseaseData Classification Using Evolvable Wavelet Neural Networks.- GO-PEAS: AScalable Yet Accurate Grid-based Outlier Detection Method Using Novel PruningSearching Techniques.- Multi-objective Genetic Programming for Figure-ground ImageSegmentation.- A New Modification of Fuzzy C-Means via Particle SwarmOptimization for Noisy Image Segmentation.- Competitive Island CooperativeNeuro-Evolution of Feedforward Networks for Time Series Prediction.- ReverseNeuron Level Decomposition for Cooperative Neuro-Evolution of FeedforwardNetworks for Time Series Prediction.- A Delaunay Triangulation Based DensityMeasurement for Evolutionary Multi-objective Optimization.- Use of InfeasibleSolutions During Constrained Evolutionary Search: A Short Survey.- Planning andScheduling.- A Differential Evolution Algorithm for Solving ResourceConstrained Project Scheduling Problems.- A hybrid imperialist competitivealgorithm for flexible job shop problem.- Parallel Multi-objective Job ShopScheduling Using Genetic Programming.- Optimization of Location Allocation ofWeb Services Using A Modified Non-dominated Sorting Genetic Algorithm.- DoubleAction Genetic Algorithm for Scheduling the Wind-Thermal Generators.- Feature Selection.-Investigating Multi-operator Differential Evolution for Feature Selection.- CoevolutionaryFeature Selection and Reconstruction in Neuro-Evolution for Time SeriesPrediction.- A Subset Similarity Guided Method for Multi-objective FeatureSelection.- Applications and Games.- An Evolutionary Optimization Approach toMaximize Runway Throughput Capacity for Hub and Spoke Airports.- FinitePopulation Trust Game Replicators.- Towards Evolved Time to ContactNeurocontrollers for Quadcopters.- The Effect of Risk Perceived Payoffs in IteratedInterdependent Security Games.- Genetic Algorithm Based Trading System Design.
| Erscheinungsdatum | 08.10.2016 |
|---|---|
| Reihe/Serie | Lecture Notes in Artificial Intelligence | Lecture Notes in Computer Science |
| Zusatzinfo | XIII, 375 p. 115 illus. in color. |
| Verlagsort | Cham |
| Sprache | englisch |
| Maße | 155 x 235 mm |
| Themenwelt | Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik |
| Schlagworte | Applications • artificial intelligence (incl. robotics) • Artificial Neural Network • Bioinformatics • cognitive science • Computer Games • Computer Science • conference proceedings • Constrained optimization • content analysis and feature selection • Decision Analysis • dynamic optimization • evolutionary optimization • Genetic algorithms • Image Segmentation • Informatics • Information Visualization • Multi-Objective Optimization • neural network • Particle swarm optimization • Planning and Scheduling • Research • similarity metrics • Solution complexity • Supervised learning by classification • Time series prediction |
| ISBN-10 | 3-319-28269-7 / 3319282697 |
| ISBN-13 | 978-3-319-28269-5 / 9783319282695 |
| Zustand | Neuware |
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