Applications of Evolutionary Computation: 23rd European Conference, Evoapplications 2020, Held as Part of Evostar 2020, Seville, Spain, April 15-17, 2, Castillo Pedro A., Jimйnez Laredo Juan Luis, Fernбndez de Vega Francisco
Описание: On Restricting Real-Valued Genotypes in Evolutionary Algorithms.- Towards Explainable Exploratory Landscape Analysis: Extreme Feature Selection for Classifying BBOB Functions.- Co-Optimising Robot Morphology and Controller in a Simulated Open-ended Environment.- Multi-objective workforce allocation in construction projects.- Generating Duplex Routes for Robust Bus Transport Network by Improved Multi-objective Evolutionary Algorithm based on Decomposition.- Combining Multi-objective Evolutionary Algorithms with deep generative models towards focused molecular design.- A Multi-Objective Evolutionary Algorithm Approach for Optimizing Part Quality Aware Assembly Job Shop Scheduling Problems.- Evolutionary Grain-Mixing to Improve Profitability in Farming Winter Wheat.- Automatic Modular Design of Behavior Trees for Robot Swarms with Communication Capabilites.- Salp Swarm Optimization Search Based Feature Selection for Enhanced Phishing Websites Detection.- Real Time Optimisation of Traffic Signals to Prioritise Public Transport.- Adaptive Covariance Pattern Search.- Evaluating the Success-History based Adaptive Differential Evolution in the Protein Structure Prediction problem.- Beyond Body Shape and Brain: Evolving the Sensory Apparatus of Voxel-based Soft Robots.- Desirable Objective Ranges in Preference-based Evolutionary Multiobjective Optimization.- Improving Search Efficiency and Diversity of Solutions in Multiobjective Binary Optimization by Using Metaheuristics plus Integer Linear Programming.- Automated, Explainable Rule Extraction from MAP-Elites archives.- EDM-DRL: Toward Stable Reinforcement Learning through Ensembled Directed Mutation.- Continuous Ant-Based Neural Topology.- Playing with Dynamic Systems - Battling Swarms in Virtual Reality.- EvoCraft: A New Challenge for Open-Endedness.- A Profile-Based 'GrEvolutionary' Hearthstone Agent.- Modelling Asthma Patients' Responsiveness to Treatment Using Feature Selection and Evolutionary Computation.- Bayesian Networks for Mood Prediction Using Unobtrusive Ecological Momentary Assessments.- A Multi-Objective Multi-Type Facility Location Problem for the Delivery of Personalised Medicine.- RDE-OP: A Region-Based Differential Evolution Algorithm Incorporation Opposition-Based Learning for Optimising the Learning Process of Multi-Layer Neural Networks.- Estimation of Grain-level Residual Stresses in a Quenched Cylindrical Sample of Aluminum Alloy AA5083 using Genetic Programming.- EDA-based optimization of blow-off valve positions for centrifugal compressor systems.- 3D-2D Registration using X-ray Simulation and CMA-ES.- Lateralized Approach for Robustness AgainstAttacks in Emotion Categorization from Images.- Improved Crowding Distance in Multi-objective Optimization for Feature Selection in Classification.- Deep Optimisation: Multi-Scale Evolution by Inducing and Searching in Deep Representations.- Evolutionary Planning in Latent Space.- Utilizing the Untapped Potential of Indirect Encoding for Neural Networks with Meta Learning.- Effective Universal Unrestricted Adversarial Attacks using a MOE Approach.- Improving Distributed Neuroevolution Using Island Extinction and Repopulation.- An Experimental Study of Weight Initialization and Lamarckian Inheritance on Neuroevolution.- Towards Feature-Based Performance Regression Using Trajectory Data.- Demonstrating the Evolution of GANs through t-SNE.- Optimising diversity in classifier ensembles of classification trees.- WILDA: Wide Learning of Diverse Architectures for Classification of Large Datasets.- Evolving Character-Level DenseNet Architectures using Genetic Programming.- Transfer Learning for Automated Test Case Prioritization using XCSF.- On the Effects of Absumption for XCS with Continuous-Valued Inputs.- A NEAT Visualisation of Neuroevolution Trajectories.- Evaluating Models with Dynamic Sampling Holdout.- Event-driven multi-algorithm optimization: mixing Swarm and Evolutionary strategies.- TensorGP
Описание: Hessian Complexity Measure for Genetic Programming-based Imputation Predictor Selection in Symbolic Regression with Incomplete Data.- Seeding Grammars in Grammatical Evolution to Improve Search Based Software Testing.- Incremental Evolution and Development of Deep Artificial Neural Networks.- Investigating the Use of Geometric Semantic Operators in Vectorial Genetic Programming.- Comparing Genetic Programming Approaches for Non-Functional Genetic Improvement.- Automatically Evolving Lookup Tables for Function Approximation.- Optimising Optimisers with Push GP.- An Evolutionary View on Reversible Shift-invariant Transformations.- Benchmarking Manifold Learning Methods on a Large Collection of Datasets.- Ensemble Genetic Programming.- SGP-DT: Semantic Genetic Programming Based on Dynamic Targets.- Effect of Parent Selection Methods on Modularity.- Time Control or Size Control? Reducing Complexity and Improving Accuracy of Genetic Programming Models.- Challenges of Program Synthesis with Grammatical Evolution.- Detection of Frailty Using Genetic Programming: The Case of Older People in Piedmont, Italy.- Is k Nearest Neighbours Regression Better than GP.- Guided Subtree Selection for Genetic Operators in Genetic Programming for Dynamic Flexible Job Shop Scheduling.- Classification of Autism Genes using Network Science and Linear Genetic Programming.
Описание: Optimizing Prices and Periods in Time-of-use Electricity Tariff Design Using Bilevel Programming.- An Algebraic Approach for the Search Space of Permutations with Repetition.- A Comparison of Genetic Representations for Multi-Objective Shortest Path Problems on Multigraphs.- The Univariate Marginal Distribution Algorithm Copes well with Deception and Epistasis.- A Beam Search Approach to the Traveling Tournament Problem.- Cooperative Parallel SAT Local Search with Path Relinking.- Dynamic Compartmental Models for Large Multi-Objective Landscapes and Performance Estimation.- Fitness Landscape Analysis of Automated Machine Learning Search Spaces.- On the Combined Impact of Population Size and Sub-problem Selection in MOEA/D.- A Grouping Genetic Algorithm for Multi Depot Pickup and Delivery Problems with Time Windows and Heterogeneous Vehicle Fleets.- MILPIBEA: Algorithm for Multi-Objective Features Selection in (Evolving) Software Product Lines.- A Group Genetic Algorithm for Resource Allocation in Container-Based Clouds.- The Local Optima Level in Chemotherapy Schedule Optimisation.- Genetic Programming with Adaptive Search Based on the Frequency of Features for Dynamic Flexible Job Shop Scheduling.
A deep learning neural network for classifying good and bad photos.- Adapting and Enhancing Evolutionary Art for Casual Creation.- Comparing Fuzzy Rule Based Approaches for Music Genre Classification.- Quantum Zentanglement: Combining Picbreeder and Wave Function Collapse to Create Zentangles.- Emerging Technology System Evolution.- Fusion of Hilbert-Huang Transform and Deep Convolutional Neural Network for Predominant Musical Instruments Recognition.- Genetic Reverb: Synthesizing Artificial Reverberant Fields Via Genetic Algorithms.- Portraits of No One: An Interactive Installation.- Understanding Aesthetic Evaluation with Deep Learning.- An Aesthetic-Based Fitness Measure and a Framework for Guidance of Evolutionary Design in Architecture.- Objective Evaluation of Tonal Fitness for Chord Progressions.- Coevolving Artistic Images Using OMNIREP.- Sound Cells in Genetic Improvisation: An Evolutionary Model for Improvised Music.- Controlling Self-Organization in Generative Creative Systems.- Emulation Games. See and Be Seen, a Subjective Approach to Analog Computational Neuroscience.
Описание: This book constitutes the refereed proceedings of the 21st European Conference on Evolutionary Computation in Combinatorial Optimization, EvoCOP 2021, held as part of Evo*2021, as Virtual Event, in April 2021, co-located with the Evo*2021 events: EvoMUSART, EvoApplications, and EuroGP.
Описание: This book constitutes the refereed proceedings of the 24th European Conference on Genetic Programming, EuroGP 2021, held as part of Evo*2021, as Virtual Event, in April 2021, co-located with the Evo*2021 events, EvoCOP, EvoMUSART, and EvoApplications.
Описание: This book discusses the applications of fracture mechanics in the design and maintenance of asphalt concrete overlays. It also reviews relevant numerical and experimental studies, and describes in detail design parameters such as aggregate type, air void, loading mode, and additives, based on the authors experience and that of other researchers.
Описание: Requirements engineering.- Software architectures.- Specification.- Software quality.- Validation.- Verification of functional and non-functional properties.- Model-driven development and model transformation.- Software processes.- Security and software evolution.
Описание: Sorting Parity Encodings by Reusing Variables.- Community and LBD-based Clause Sharing Policy for Parallel SAT Solving.- Clause size reduction with all-UIP Learning.- Trail Saving on Backtrack.- Four Flavors of Entailment.- Designing New Phase Selection Heuristics.- On the Effect of Learned Clauses on Stochastic Local Search.- SAT Heritage: a community-driven effort for archiving, building and running more than thousand SAT solvers.- Distributed Cube and Conquer with Paracooba.- Reproducible E cient Parallel SAT Solving.- Improving Implementation of SAT Competitions 2017-2019 Winners.- On CDCL-based Proof Systems with the Ordered Decision Strategy.- Equivalence Between Systems Stronger Than Resolution.- Simplified and Improved Separations Between Regular and General Resolution by Lifting.- Mycielski graphs and PR proofs.- Towards a Better Understanding of (Partial Weighted) MaxSAT Proof Systems.- Towards a Complexity-theoretic Understanding of Restarts in SAT solvers.- On the Sparsity of XORs in Approximate Model Counting.- A Faster Algorithm for Propositional Model Counting Parameterized by Incidence Treewidth.- Abstract Cores in Implicit Hitting Set MaxSat Solving.- MaxSAT Resolution and SubCube Sums.- A Lower Bound on DNNF Encodings of Pseudo-Boolean Constraints.- On Weakening Strategies for PB Solvers.- Reasoning About Strong Inconsistency in ASP.- Taming High Treewidth with Abstraction, Nested Dynamic Programming, and Database Technology.- Reducing Bit-Vector Polynomials to SAT using Groebner Bases.- Speeding Up Quantified Bit-Vector SMT Solvers by Bit-Width Reductions and Extensions.- Strong (D)QBF Dependency Schemes via Tautology-free Resolution Paths.- Short Q-Resolution Proofs with Homomorphisms.- Multi-Linear Strategy Extraction for QBF Expansion Proofs via Local Soundness.- Positional Games and QBF: The Corrective Encoding.- Matrix Multiplication: Verifying Strong Uniquely Solvable Puzzles.- Satisfiability Solving Meets Evolutionary Optimisation in Designing Approximate Circuits.- SAT Solving with Fragmented Hamiltonian Path Constraints for Wire Arc Additive Manufacturing.- SAT-based Encodings for Optimal Decision Trees with Explicit Paths.- Incremental Encoding of Pseudo-Boolean Goal Functions based on Comparator Networks.
Описание: This book constitutes the refereed proceedings of the 23rd International Conference on Distributed and Computer and Communication Networks, DCCN 2020, held in Moscow, Russia, in September 2020. analytical modeling of distributed systems, and distributed systems applications.
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