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E-raamat: Genetic Programming: 25th European Conference, EuroGP 2022, Held as Part of EvoStar 2022, Madrid, Spain, April 20-22, 2022, Proceedings

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Genetic Programming: 25th European Conference, EuroGP 2022, Held as Part of EvoStar 2022, Madrid, Spain, April 20-22, 2022, ProceedingsSuurem pilt
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This book constitutes the refereed proceedings of the 25th European Conference on Genetic Programming, EuroGP 2022, held as part of Evo*2021, as Virtual Event, in April 2022, co-located with the Evo*2022 events, EvoCOP, EvoMUSART, and EvoApplications. The 12 revised full papers and 7 short papers presented in this book were carefully reviewed and selected from 35 submissions. The wide range of topics in this volume reflects the current state of research in the field. The collection of papers cover topics including developing new operators for variants of GP algorithms, as well as exploring GP applications to the optimization of machine learning methods and the evolution of complex combinational logic circuits.





 
Long Presentations.- Evolving Adaptive Neural Network Optimizers for
Image Classification.- Combining Geometric Semantic GP with Gradient-descent
Optimization.- One-Shot Learning of Ensembles of Temporal Logic Formulas for
Anomaly Detection in Cyber-Physical Systems.- Multi-objective GP with AWS for
Symbolic Regression.- SLUG: Feature Selection Using Genetic Algorithms and
Genetic Programming.- Evolutionary Design of Reduced Precision
Levodopa-Induced Dyskinesia Classifiers.- Using Denoising Autoencoder Genetic
Programming to Control Exploration and Exploitation in Search.- Program
Synthesis with Genetic Programming: The Influence of Batch Sizes.- Genetic
Programming-Based Inverse Kinematics for Robotic Manipulators.- On the
Schedule for Morphological Development of Evolved Modular Soft Robots.- An
Investigation of Multitask Linear Genetic Programming for Dynamic Job Shop
Scheduling.- Cooperative Co-Evolution and Adaptive Team Composition for a
Multi-Rover Resources Allocation Problem.- Short Presentations.-
 Synthesizing Programs from Program Pieces using Genetic Programming and
Refinement Type Checking.- Creating Diverse Ensembles for Classification with
Genetic Programming and Neuro-MAP-Elites.- Evolving Monotone Conjunctions in
Regimes Beyond Proved Convergence.- Accurate and Interpretable
Representations of Environments with Anticipatory Learning Classifier
Systems.- Exploiting Knowledge from Code to Guide Program Search.-
Multi-Objective Genetic Programming for Explainable Reinforcement Learning.-
Permutation-Invariant Representation of Neural Networks with Neuron
Embeddings.
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