Search Results - (automatizacni OR automatic) programming— program synthesis general terms algorithms~
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Subject Terms: Categories and Subject Descriptors I.2.2 [Artificial Intelligence, Automatic Programming— program synthesis General Terms Algorithms, Design, Experimentation Keywords Artificial Intelligence, Genetic Programming, Representations
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Relation: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.153.820; http://www.cs.bham.ac.uk/~wbl/biblio/gecco2008/docs/p1339.pdf
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Subject Terms: Categories and Subject Descriptors I.2.2 [Artificial Intelligence, Automatic Programming – program synthesis. General Terms Algorithms, Performance, Design, Experimentation. Keywords Genetic Programming, Multi-objective Classification
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Relation: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.420.8631; http://www.cs.york.ac.uk/rts/docs/GECCO_2006/docs/p863.pdf
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Subject Terms: Categories and Subject Descriptors I.2.2 [Artificial Intelligence, Automatic Programming – program synthesis. General Terms Algorithms, Performance, Experimentation, Theory. Keywords Population dynamics, initial populations, binomial-3, GP problem difficulty
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Relation: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.420.8098; http://www.cs.bham.ac.uk/~wbl/biblio/gecco2005/docs/p1627.pdf
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Subject Terms: Categories and Subject Descriptors I.2.2 [Artificial Intelligence, Automatic Programming— program synthesis General Terms Algorithms, Design, Experimentation Keywords Artificial Intelligence, Genetic Programming, Representations
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Source: Pollack Periodica; 2017, Vol. 12 Issue 2, p3-15, 13p
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Subject Terms: Categories and Subject Descriptors I.2.2 [Artificial Intelligence, Automatic Programming – Program synthesis General Terms Algorithms, Design, Experimentation Keywords Empirical Study, Heuristics, Optimization, Representations
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Relation: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.100.7743; http://www.metacog.org/papers/gecco07e.pdf
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Subject Terms: Categories and Subject Descriptors I.2.2 [Artificial Intelligence, Automatic Programming— Program Synthesis General Terms Algorithms, Design, Experimentation, Performance Keywords Cartesian genetic programming (CGP, embedded cartesian
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Relation: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.152.9345; http://www.cs.bham.ac.uk/~wbl/biblio/gecco2008/docs/p1219.pdf
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Subject Terms: Categories and Subject Descriptors I.2.2 [Artificial Intelligence, Automatic programming— Program synthesis General Terms Algorithms, Experimentation, Measurement Keywords Genetic Programming, Benchmarks
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Relation: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.369.7187; http://www.dcs.gla.ac.uk/~whited/papers/genetic_programming_needs_better_benchmarks.pdf
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9
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Subject Terms: Categories and Subject Descriptors I.2.2 [Artificial Intelligence, Automatic programming— Program synthesis General Terms Algorithms, Experimentation, Measurement Keywords Genetic Programming, Benchmarks
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Relation: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.299.3642; http://www.cs.gmu.edu/~sean/papers/gecco12benchmarks.pdf
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Subject Terms: Categories and Subject Descriptors I.2.2 [Artificial Intelligence, Automatic programming— Program synthesis General Terms Algorithms, Experimentation, Measurement Keywords Genetic Programming, Benchmarks
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Relation: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.294.7158; http://cs.gmu.edu/~sean/papers/gecco12benchmarks3.pdf
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Probing for Limits to Building Block Mixing with a Tunably-Difficult Problem for Genetic Programming
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Subject Terms: Categories and Subject Descriptors I.2.2 [Artificial Intelligence, Automatic Programming – program synthesis. General Terms Algorithms, Performance, Experimentation, Theory. Keywords Tunably-difficult problems, Highlander problem, building blocks, initial
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Relation: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.420.6674; http://www.cs.bham.ac.uk/~wbl/biblio/gecco2005/docs/p1713.pdf
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Source: Nature Machine Intelligence; Feb2025, Vol. 7 Issue 2, p205-220, 16p
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Source: Water (20734441); Nov2025, Vol. 17 Issue 22, p3249, 32p
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Authors: et al.
Source: Computation; Jan2025, Vol. 13 Issue 1, p10, 27p
Subject Terms: CONSTRAINT programming, UNIVERSITIES & colleges, BLENDED learning, HIGHER education, DEEP diving
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15
Authors: et al.
Source: Water (20734441); Oct2025, Vol. 17 Issue 20, p2994, 36p
Subject Terms: MACHINE learning, GROUNDWATER quality, BIBLIOMETRICS, ENSEMBLE learning, CONTENT analysis, DEEP learning, TREND analysis
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16
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Subject Terms: Automatic programming—Program synthesis General Terms Algorithms, Experimentation, Human Factors
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Relation: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.6.2438; http://www.cs.washington.edu/homes/pedrod/papers/kcap03b.pdf
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Source: Journal of Intelligence; Aug2025, Vol. 13 Issue 8, p102, 42p
Subject Terms: PSYCHOMETRICS, TEST validity, TRANSFORMER models, CALIBRATION, CRITICAL analysis, UNIVERSITY research
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Source: Pattern Recognition & Image Analysis; Sep2025, Vol. 35 Issue 3, p359-375, 17p
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Source: Computation; May2023, Vol. 11 Issue 5, p97, 15p
Subject Terms: DEEP learning, COMPUTING platforms, HETEROGENEOUS computing, BIG data, DATA science
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Source: Memetic Computing; Sep2025, Vol. 17 Issue 3, p1-22, 22p
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