Applications of Evolutionary Computation: 27th European Conference, EvoApplications 2024, Held as Part of EvoStar 2024, Aberystwyth, UK, April 3–5, 2024, Proceedings, Part II: Lecture Notes in Computer Science, cartea 14635
Editat de Stephen Smith, João Correia, Christian Cintranoen Limba Engleză Paperback – 16 apr 2024
The 51 full papers presented in these proceedings were carefully reviewed and selected from 77 submissions. The papers have been organized in the following topical sections: applications of evolutionary computation; analysis of evolutionary computation methods: theory, empirics, and real-world applications; computational intelligence for sustainability; evolutionary computation in edge, fog, and cloud computing; evolutionary computation in image analysis, signal processing and pattern recognition; evolutionary machine learning; machine learning and AI in digital healthcare and personalized medicine; problem landscape analysis for efficient optimization; softcomputing applied to games; and surrogate-assisted evolutionary optimisation.
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Specificații
ISBN-13: 9783031568541
ISBN-10: 3031568540
Ilustrații: XXI, 409 p. 151 illus., 125 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.6 kg
Ediția:2024
Editura: Springer Nature Switzerland
Colecția Springer
Seria Lecture Notes in Computer Science
Locul publicării:Cham, Switzerland
ISBN-10: 3031568540
Ilustrații: XXI, 409 p. 151 illus., 125 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.6 kg
Ediția:2024
Editura: Springer Nature Switzerland
Colecția Springer
Seria Lecture Notes in Computer Science
Locul publicării:Cham, Switzerland
Cuprins
Evolutionary Machine Learning: Hindsight Experience Replay with Evolutionary Decision Trees for Curriculum Goal Generation.- Cultivating Diversity: A Comparison of Diversity Objectives in Neuroevolution.- Evolving Reservoirs for Meta Reinforcement Learning.- Hybrid Surrogate Assisted Evolutionary Multiobjective Reinforcement Learning for Continuous Robot Control.- Towards Physical Plausibility in Neuroevolution Systems.- Leveraging More of Biology in Evolutionary Reinforcement Learning.- A Hierarchical Dissimilarity Metric for Automated Machine Learning Pipelines, and Visualizing Search Behaviour.- DeepEMO: A Multi-Indicator Convolutional Neural Network-based Evolutionary Multi-Objective Algorithm.- A Comparative Analysis of Evolutionary Adversarial One-Pixel Attacks.- Robust Neural Architecture Search using Differential Evolution for Medical Images.- Progressive Self-Supervised Multi-Objective NAS for Image Classification.- Genetic Programming with Aggregate Channel Features for Flower Localization Using Limited Training Data.- Evolutionary Multi-Objective Optimization of Large Language Model Prompts for Balancing Sentiments.- Evolutionary Feature-Binning with Adaptive Burden Thresholding for Biomedical Risk Stratification.- An Evolutionary Deep Learning Approach for Efficient Quantum Algorithms Transpilation.- Measuring Similarities in Model Structure of Metaheuristic Rule Set Learners.- Machine Learning and AI in Digital Healthcare and Personalized Medicine: Incremental growth on Compositional Pattern Producing Networks based optimization of biohybrid actuators.- Problem Landscape Analysis for Efficient Optimization: Hilbert Curves for Efficient Exploratory Landscape Analysis Neighbourhood Sampling.- Predicting Algorithm Performance in Constrained Multiobjective Optimization: A Tough Nut to Crack.- On the Latent Structure of the bbob-biobj Test Suite.- Soft Computing applied to Games.- Strategies for Evolving Diverse and Effective Behaviours in Pursuit Domains.- Using Evolution and Deep Learning to Generate Diverse Intelligent Agents.- Vision Transformers for Computer Go.- Surrogate-Assisted Evolutionary Optimisation: Integrating Bayesian and Evolutionary Approaches for Multi-Objective
Optimisation.