Applications of Evolutionary Computation

27th European Conference, EvoApplications 2024, Held as Part of EvoStar 2024, Aberystwyth, UK, April 3–5, 2024, Proceedings, Part II

AvStephen Smith,João Correia

Häftad, Engelska, 2024

Del 14635 i serien Lecture Notes in Computer Science

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Beskrivning

The two-volume set LNCS 14634 and 14635 constitutes the refereed proceedings of the 27th European Conference on Applications of Evolutionary Computation, EvoApplications 2024, held as part of EvoStar 2024, in Aberystwyth, UK, April 3–5, 2024, and co-located with the EvoStar events, EvoCOP, EvoMUSART, and EuroGP.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.

Produktinformation

Utgivningsdatum:2024-04-16
Mått:155 x 235 x 24 mm
Vikt:651 g
Format:Häftad
Språk:Engelska
Serie:Lecture Notes in Computer Science
Antal sidor:409
Förlag:Springer International Publishing AG
ISBN:9783031568541

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Innehållsförteckning

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-ObjectiveOptimisation.