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Modeling building-block interdependency

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/978-3-662-02830-8openalex-snapshot
Genetic Algorithms + Data Structures = Evolution Programs
inferredcites →https://doi.org/10.1007/bf00993046openalex-snapshot
What makes a problem hard for a genetic algorithm? Some anomalous results and their explanation
inferredcites →https://doi.org/10.1007/bf01531277openalex-snapshot
Sufficient conditions for deceptive and easy binary functions
inferredcites →https://doi.org/10.1007/bf02430367openalex-snapshot
Test driving three 1995 genetic algorithms: New test functions and geometric matching
inferredcites →https://doi.org/10.1016/0303-2647(94)90009-4openalex-snapshot
Foundations of genetic algorithms. 2
inferredcites →https://doi.org/10.1016/b978-0-08-094832-4.50013-1openalex-snapshot
Relative Building-Block Fitness and the Building-Block Hypothesis
inferredcites →https://doi.org/10.1016/b978-1-55860-356-1.50006-6openalex-snapshot
The Schema Theorem and Price's Theorem
inferredcites →https://doi.org/10.1016/b978-1-55860-356-1.50016-9openalex-snapshot
Genetic Algorithm Difficulty and the Modality of Fitness Landscapes
inferredcites →https://doi.org/10.1023/a:1022626114466openalex-snapshot
What Makes a Problem Hard for a Genetic Algorithm? Some Anomalous Results and Their Explanation
inferredcites →https://doi.org/10.1093/oso/9780195079517.001.0001openalex-snapshot
The Origins of Order
inferredcites →https://doi.org/10.1145/152941.1064724openalex-snapshot
Book review: Genetic Algorithms + Data Structures = Evolution Programs by Zbigniew Michalewicz (Springer-Verlag, 1992)
inferredcites →https://doi.org/10.1162/evco.1993.1.2.127openalex-snapshot
Searching for Diverse, Cooperative Populations with Genetic Algorithms
inferredcites →https://doi.org/10.5860/choice.27-0936openalex-snapshot
Genetic algorithms in search, optimization, and machine learning
inferredcites →https://doi.org/10.7551/mitpress/1090.001.0001openalex-snapshot
Adaptation in Natural and Artificial Systems

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

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Fragment as a Small Evidence of the Building Blocks Existence
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The Gestalt heuristic: emerging abstraction to improve combinatorial search
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Self-healing strategies for memetic algorithms in unstable and ephemeral computational environments
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A Kernighan-Lin local improvement heuristic that softens several hard problems in genetic algorithms
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Excluding the best and worst individuals from parent selection
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The Analysis of a Recombinative Hill-Climber on H-IFF
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ORDERTREE
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Towards memoryless model building
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Opportunistic evolution
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Representations for evolutionary algorithms
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Hierarchical allelic pairwise independent functions
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Denoising Autoencoders for Fast Combinatorial Black Box Optimization
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A diversity preservation scheme for DSMGA-II to conquer the hierarchical difficulty
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A Fast Multi-objective Evolutionary Approach for Designing Large-Scale Optical Mode Sorter
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Energy consumption of evolutionary algorithms implemented in low-level languages
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Representations for Evolutionary Algorithms
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Empirical Linkage Learning Provably Builds Truthful Models on Concatenated Traps and H-IFF
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Metaheuristics in combinatorial optimization
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Spin-Flip Symmetry and Synchronization
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Mapping the Royal Road and Other Hierarchical Functions
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Estimation of Distribution Algorithms with Kikuchi Approximations
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Modular Interdependency in Complex Dynamical Systems
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Death and Progress: How Evolvability is Influenced by Intrinsic Mortality
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Dependency Structure Matrix, Genetic Algorithms, and Effective Recombination
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Fast and Efficient Black Box Optimization Using the Parameter-less Population Pyramid
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Generating, Maintaining, and Exploiting Diversity in a Memetic Algorithm for Protein Structure Prediction
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Intrinsic Mortality Governs Evolvability
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The Neuronal Replicator Hypothesis
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Analyzing self-★ island-based memetic algorithms in heterogeneous unstable environments
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Heuristic algorithms in evolutionary computation and modular organization of biological macromolecules: Applications to in vitro evolution
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A study on meme propagation in multimemetic algorithms
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Real Royal Road Functions - Where Crossover Provably is Essential
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On the use of self-* Island-based evolutionary computation methods on complex environments
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Building Applied Models from Observational Research and Fieldwork in Educational Settings
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Practical Search Index as a Hardness Measure for Genetic Algorithms
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Denoising Autoencoders for fast Combinatorial Black Box Optimization
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Deep Boltzmann Machines in Estimation of Distribution Algorithms for Combinatorial Optimization
inferred← citeshttps://doi.org/10.48550/arxiv.1811.00784openalex-snapshot
Deep Optimisation: Solving Combinatorial Optimisation Problems using Deep Neural Networks
inferred← citeshttps://doi.org/10.52842/conf.ecaade.2014.1.079openalex-snapshot
Multi-Perspective Urban Optioneering
inferred← citeshttps://doi.org/10.7551/mitpress/1432.003.0024openalex-snapshot
Mutualism, Parasitism, and Evolutionary Adaptation
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