Fast enumeration of all cost-bounded solutions for combinatorial problems using ZDDs

Συγγραφείς: Shin-ichi Minato, Jun Kawahara, Mutsunori Banbara, Takashi Horiyama, Ichigaku Takigawa, Yutaro Yamaguchi

Πηγή: Discrete Applied Mathematics. 360:467-486

Θεματικοί όροι: Combinatorial optimization, combinatorial problems, exact enumeration, Combinatorics in computer science, decision diagrams, cost-bounded solutions, Problem solving in the context of artificial intelligence (heuristics, search strategies, etc.)

Περιγραφή αρχείου: application/xml

Adaptive Operator Learning for Infinite-Dimensional Bayesian Inverse Problems: Adaptive operator learning for infinite-dimensional Bayesian inverse problems

Συγγραφείς: Zhiwei Gao, Liang Yan, Tao Zhou

Πηγή: SIAM/ASA Journal on Uncertainty Quantification. 12:1389-1423

Θεματικοί όροι: unscented Kalman inversion, FOS: Computer and information sciences, Inverse problems for PDEs, Bayesian inference, Numerical methods for ill-posed problems for initial value and initial-boundary value problems involving PDEs, Bayesian inverse problems, Machine Learning (stat.ML), Numerical Analysis (math.NA), Statistics - Computation, 01 natural sciences, operator learning, Statistics - Machine Learning, 0103 physical sciences, FOS: Mathematics, Mathematics - Numerical Analysis, 0101 mathematics, Problem solving in the context of artificial intelligence (heuristics, search strategies, etc.), Computation (stat.CO)

Περιγραφή αρχείου: application/xml

Σύνδεσμος πρόσβασης: http://arxiv.org/abs/2310.17844
https://zbmath.org/7973170
https://doi.org/10.1137/24m1643815

Constraint Propagation on GPU: A Case Study for the Cumulative Constraint: Constraint propagation on GPU: a case study for the cumulative constraint

Συγγραφείς: Fabio Tardivo, Agostino Dovier, Andrea Formisano, Laurent Michel, Enrico Pontelli

Πηγή: Lecture Notes in Computer Science ISBN: 9783031332708

Θεματικοί όροι: parallelism, energetic reasoning, Deterministic scheduling theory in operations research, cumulative, constraint propagation, GPU, Problem solving in the context of artificial intelligence (heuristics, search strategies, etc.)

Περιγραφή αρχείου: application/xml

Σύνδεσμος πρόσβασης: https://zbmath.org/7980120
https://doi.org/10.1007/s10601-024-09371-w
https://hdl.handle.net/11390/1257464
https://doi.org/10.1007/978-3-031-33271-5_22

Planning Mathematical Proofs with Methods: Planning mathematical proofs with methods

Συγγραφείς: Huang, Xiaorong, Kerber, Manfred, Richts, Jörn, Sehn, Arthur

Θεματικοί όροι: ddc:004, proof planning, declarative language, encoding plan operators, Problem solving in the context of artificial intelligence (heuristics, search strategies, etc.), Theorem proving (deduction, resolution, etc.)

Περιγραφή αρχείου: application/xml

Σύνδεσμος πρόσβασης: https://zbmath.org/827983

Generalized multiview sequential three-way decisions based on local partition order product space

Συγγραφείς: Qian, Jin, Zhou, Chuanpeng, Yu, Ying, Zheng, Mingchen, Hong, Chengxin, Wang, Hui

Πηγή: International Journal of Approximate Reasoning. 178:109350

Θεματικοί όροι: granular computing, multilevel, product space, sequential three-way decision, Learning and adaptive systems in artificial intelligence, multiview, Problem solving in the context of artificial intelligence (heuristics, search strategies, etc.), Reasoning under uncertainty in the context of artificial intelligence

Περιγραφή αρχείου: application/xml

Generative models for grid-based and image-based pathfinding

Συγγραφείς: Daniil Kirilenko, Anton Andreychuk, Aleksandr I. Panov, Konstantin Yakovlev

Πηγή: Artificial Intelligence. 338:104238

Θεματικοί όροι: pathfinding, A, transformer, learning heuristics, planning on images, Problem solving in the context of artificial intelligence (heuristics, search strategies, etc.), Computing methodologies for image processing, path planning

Περιγραφή αρχείου: application/xml

Fixed-target runtime analysis

Συγγραφείς: Buzdalov, Maxim, Doerr, Benjamin, Doerr, Carola, Vinokurov, Dmitry

Συνεισφορές: Doerr, Carola, ITMO University Russia, Laboratoire d'informatique de l'École polytechnique Palaiseau (LIX), École polytechnique (X), Institut Polytechnique de Paris (IP Paris)-Institut Polytechnique de Paris (IP Paris)-Centre National de la Recherche Scientifique (CNRS), Recherche Opérationnelle (RO), LIP6, Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), ANR-11-LABX-0056,LMH,LabEx Mathématique Hadamard(2011)

Πηγή: Proceedings of the 2020 Genetic and Evolutionary Computation Conference. :1295-1303

Θεματικοί όροι: FOS: Computer and information sciences, Evolutionary algorithms, genetic algorithms (computational aspects), [INFO.INFO-NE] Computer Science [cs]/Neural and Evolutionary Computing [cs.NE], randomized search heuristics, Computer Science - Neural and Evolutionary Computing, [INFO.INFO-NE]Computer Science [cs]/Neural and Evolutionary Computing [cs.NE], 68Q17, evolutionary computation, Analysis of algorithms, Neural and Evolutionary Computing (cs.NE), F.2.2, Problem solving in the context of artificial intelligence (heuristics, search strategies, etc.), runtime analysis

Περιγραφή αρχείου: application/xml; application/pdf

Σύνδεσμος πρόσβασης: http://arxiv.org/pdf/2004.09613
http://arxiv.org/abs/2004.09613
https://zbmath.org/7535652
https://doi.org/10.1007/s00453-021-00881-0
https://link.springer.com/article/10.1007%2Fs00453-021-00881-0
https://hal.archives-ouvertes.fr/hal-03377095
https://dblp.uni-trier.de/db/journals/corr/corr2004.html#abs-2004-09613
https://arxiv.org/abs/2004.09613
https://arxiv.org/abs/2004.09613
https://ui.adsabs.harvard.edu/abs/2020arXiv200409613B/abstract
http://arxiv.org/pdf/2004.09613.pdf
https://hal.sorbonne-universite.fr/hal-02871956v1

A review of three-way decision: Triadic understanding, organization, and perspectives: A review of three-way decision: triadic understanding, organization, and perspectives

Συγγραφείς: Langwangqing Suo, Han Yang, Qiaoyi Li, Hai-Long Yang, Yiyu Yao

Πηγή: International Journal of Approximate Reasoning. 173:109268

Θεματικοί όροι: triadic thinking, \(3 \times 3\) method, three-way bibliometrics analytics, three-way literature review, three-way decision, Problem solving in the context of artificial intelligence (heuristics, search strategies, etc.), Reasoning under uncertainty in the context of artificial intelligence, Decision theory

Περιγραφή αρχείου: application/xml

Σύνδεσμος πρόσβασης: https://zbmath.org/7905224
https://doi.org/10.1016/j.ijar.2024.109268

Tail bounds on hitting times of randomized search heuristics using variable drift analysis

Συγγραφείς: Lehre, P. K., Witt, C.

Πηγή: Lehre, P K & Witt, C 2021, ' Tail bounds on hitting times of randomized search heuristics using variable drift analysis ', Combinatorics Probability and Computing, vol. 30, no. 4, pp. 550–569 . https://doi.org/10.1017/S0963548320000565

Θεματικοί όροι: Evolutionary algorithms, genetic algorithms (computational aspects), 4. Education, Randomized algorithms, 0202 electrical engineering, electronic engineering, information engineering, 0102 computer and information sciences, 02 engineering and technology, Problem solving in the context of artificial intelligence (heuristics, search strategies, etc.), 01 natural sciences

Περιγραφή αρχείου: application/xml; application/pdf

Σύνδεσμος πρόσβασης: https://backend.orbit.dtu.dk/ws/files/234770969/tail_bounds_on_hitting_times_of_randomized_search_heuristics_using_variable_drift_analysis.pdf
https://orbit.dtu.dk/en/publications/tail-bounds-on-hitting-times-of-randomized-search-heuristics-usin
https://backend.orbit.dtu.dk/ws/files/234770969/tail_bounds_on_hitting_times_of_randomized_search_heuristics_using_variable_drift_analysis.pdf
https://www.cambridge.org/core/journals/combinatorics-probability-and-computing/article/tail-bounds-on-hitting-times-of-randomized-search-heuristics-using-variable-drift-analysis/F30499B93D4498D404E00206005A999A
https://www.cambridge.org/core/services/aop-cambridge-core/content/view/F30499B93D4498D404E00206005A999A/S0963548320000565a.pdf/div-class-title-tail-bounds-on-hitting-times-of-randomized-search-heuristics-using-variable-drift-analysis-div.pdf
https://orbit.dtu.dk/en/publications/bfdcc357-ac66-4d8d-bb15-c5701c9ed438

Self-adjusting evolutionary algorithms for multimodal optimization

Συγγραφείς: Amirhossein Rajabi, Carsten Witt

Πηγή: Rajabi, A & Witt, C 2020, Self-adjusting evolutionary algorithms for multimodal optimization . in Proceedings of the 2020 Genetic and Evolutionary Computation Conference . Association for Computing Machinery, pp. 1314-1322, 2020 Genetic and Evolutionary Computation Conference, Cancun, Mexico, 08/07/2020 . https://doi.org/10.1145/3377930.3389833

Θεματικοί όροι: multimodal functions, FOS: Computer and information sciences, Evolutionary algorithms, genetic algorithms (computational aspects), Multimodal functions, randomized search heuristics, self-adjusting algorithms, Computer Science - Neural and Evolutionary Computing, 0102 computer and information sciences, 02 engineering and technology, 01 natural sciences, Self-adjusting algorithms, Randomised search heuristics, 0202 electrical engineering, electronic engineering, information engineering, Analysis of algorithms, Runtime analysis, Neural and Evolutionary Computing (cs.NE), Problem solving in the context of artificial intelligence (heuristics, search strategies, etc.), runtime analysis

Περιγραφή αρχείου: application/xml; application/pdf

Σύνδεσμος πρόσβασης: https://backend.orbit.dtu.dk/ws/files/247787189/Rajabi_Witt2020_GECCO.pdf
http://arxiv.org/abs/2004.03266
https://arxiv.org/abs/2004.03266
https://ui.adsabs.harvard.edu/abs/2020arXiv200403266R/abstract
https://arxiv.org/pdf/2004.03266.pdf
https://dblp.uni-trier.de/db/journals/corr/corr2004.html#abs-2004-03266
https://dl.acm.org/doi/pdf/10.1145/3377930.3389833
https://orbit.dtu.dk/en/publications/2f0d9a20-b131-4308-9724-13ebf8c68d76

First-hitting times under drift

Συγγραφείς: Kötzing, Timo (Dr.), Krejca, Martin Stefan

Πηγή: Theoretical Computer Science. 796:51-69

Θεματικοί όροι: Stopping times, optimal stopping problems, gambling theory, Probability in computer science (algorithm analysis, random structures, phase transitions, etc.), ddc:000, drift, Randomized algorithms, 0202 electrical engineering, electronic engineering, information engineering, Hasso-Plattner-Institut für Digital Engineering GmbH, first-hitting time, 0102 computer and information sciences, 02 engineering and technology, Problem solving in the context of artificial intelligence (heuristics, search strategies, etc.), 01 natural sciences, random process

Περιγραφή αρχείου: application/xml

Σύνδεσμος πρόσβασης: https://www.sciencedirect.com/science/article/pii/S0304397519305109
https://dblp.uni-trier.de/db/journals/tcs/tcs796.html#KotzingK19
https://doi.org/10.1016/j.tcs.2019.08.021

Analyzing randomized search heuristics via stochastic domination

Συγγραφείς: Benjamin Doerr

Συνεισφορές: École polytechnique (X), Institut Polytechnique de Paris (IP Paris), Laboratoire d'informatique de l'École polytechnique Palaiseau (LIX), Institut Polytechnique de Paris (IP Paris)-Institut Polytechnique de Paris (IP Paris)-Centre National de la Recherche Scientifique (CNRS)

Πηγή: Theoretical Computer Science. 773:115-137

Θεματικοί όροι: Evolutionary algorithms, genetic algorithms (computational aspects), Randomized algorithms, 0211 other engineering and technologies, [INFO]Computer Science [cs], Analysis of algorithms, 0102 computer and information sciences, 02 engineering and technology, evolutionary algorithms, Problem solving in the context of artificial intelligence (heuristics, search strategies, etc.), 01 natural sciences, runtime analysis

Περιγραφή αρχείου: application/xml

Σύνδεσμος πρόσβασης: https://www.sciencedirect.com/science/article/am/pii/S0304397518305954
https://arxiv.org/abs/1801.04487
https://dblp.uni-trier.de/db/journals/tcs/tcs773.html#Doerr19
https://ru.arxiv.org/abs/1801.04487
https://core.ac.uk/display/146481142
https://www.sciencedirect.com/science/article/pii/S0304397518305954
https://arxiv.org/pdf/1801.04487

On the Lower Bounds of (1,0)-Super Solutions for Random k-SAT: On the lower bounds of \((1, 0)\)-super solutions for random \(k\)-SAT

Συγγραφείς: Guangyan Zhou, Rui Kang

Πηγή: International Journal of Foundations of Computer Science. 30:247-254

Θεματικοί όροι: 0301 basic medicine, 03 medical and health sciences, satisfiability, super-solution, 0102 computer and information sciences, Problem solving in the context of artificial intelligence (heuristics, search strategies, etc.), 16. Peace & justice, weighting scheme, 01 natural sciences

Περιγραφή αρχείου: application/xml

Σύνδεσμος πρόσβασης: https://zbmath.org/7072199
https://doi.org/10.1142/s0129054119500035
https://dblp.uni-trier.de/db/journals/ijfcs/ijfcs30.html#ZhouK19
https://doi.org/10.1142/S0129054119500035
https://www.worldscientific.com/doi/abs/10.1142/S0129054119500035

Solving Constraint-Satisfaction Problems with Distributed Neocortical-Like Neuronal Networks: Solving constraint-satisfaction problems with distributed neocortical-like neuronal networks

Συγγραφείς: Rutishauser, Ueli, Slotine, Jean-Jacques, Douglas, Rodney J.

Συνεισφορές: University of Zurich, Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology. Department of Mechanical Engineering, Slotine, Jean-Jacques E

Πηγή: Neural Computation. 30:1359-1393

Θεματικοί όροι: 2805 Cognitive Neuroscience, Neurons, 0301 basic medicine, 0303 health sciences, Networks and circuits as models of computation, circuit complexity, 4. Education, Models, Neurological, Neocortex, 03 medical and health sciences, Nonlinear Dynamics, 1201 Arts and Humanities (miscellaneous), Quantitative Biology - Neurons and Cognition, FOS: Biological sciences, 570 Life sciences, biology, Animals, Humans, Computer Simulation, Neurons and Cognition (q-bio.NC), Neural Networks, Computer, Nerve Net, Problem solving in the context of artificial intelligence (heuristics, search strategies, etc.), Problem Solving, 10194 Institute of Neuroinformatics

Περιγραφή αρχείου: application/xml; ZORA_168617.pdf - application/pdf; application/pdf

Σύνδεσμος πρόσβασης: https://dspace.mit.edu/bitstream/1721.1/120124/1/neco_a_01074.pdf
https://pubmed.ncbi.nlm.nih.gov/29566357
http://arxiv.org/abs/1801.04515
https://zbmath.org/7409213
https://doi.org/10.1162/neco_a_01074
https://www.ncbi.nlm.nih.gov/pubmed/29566357
http://doi.org/10.1162/neco_a_01074
https://ieeexplore.ieee.org/document/8353111/authors
http://europepmc.org/articles/PMC5930080
http://cognet.mit.edu/journal/10.1162/neco_a_01074
https://direct.mit.edu/neco/article/30/5/1359/8351/Solving-Constraint-Satisfaction-Problems-with

Extracting mutual exclusion invariants from lifted temporal planning domains

Συγγραφείς: Sara Bernardini, Fabio Fagnani, David E. Smith

Πηγή: Artificial Intelligence. 258:1-65

Θεματικοί όροι: temporal planning, automated planning, mutual exclusion invariants, 0202 electrical engineering, electronic engineering, information engineering, 0102 computer and information sciences, 02 engineering and technology, Problem solving in the context of artificial intelligence (heuristics, search strategies, etc.), automatic domain analysis, 01 natural sciences, Automated planning, Automatic domain analysis, Mutual exclusion invariants, Temporal planning, Language and Linguistics, Linguistics and Language, Artificial Intelligence

Περιγραφή αρχείου: application/xml; application/pdf

Σύνδεσμος πρόσβασης: https://dblp.uni-trier.de/db/journals/ai/ai258.html#BernardiniFS18
https://www.sciencedirect.com/science/article/pii/S0004370218300377
https://iris.polito.it/handle/11583/2702992
https://www.sciencedirect.com/science/article/pii/S0004370218300377?via=ihub
https://hdl.handle.net/11583/2702992
https://doi.org/10.1016/j.artint.2018.01.004

Strong temporal planning with uncontrollable durations

Συγγραφείς: Alessandro Cimatti, Minh Do, Andrea Micheli, Marco Roveri, David E. Smith

Συνεισφορές: Cimatti, Alessandro, Do, Minh, Micheli, Andrea, Roveri, Marco, Smith, David E.

Πηγή: Artificial Intelligence. 256:1-34

Θεματικοί όροι: Forward state space planning, temporal planning, Uncontrollable duration, Temporal planning, ANML, strong controllability, 0102 computer and information sciences, 02 engineering and technology, 16. Peace & justice, 01 natural sciences, Strong temporal planning, PDDL, uncontrollable durations, 0202 electrical engineering, electronic engineering, information engineering, forward state-space planning, Strong controllability, Uncontrollable durations, Problem solving in the context of artificial intelligence (heuristics, search strategies, etc.), strong temporal planning

Περιγραφή αρχείου: application/xml; application/pdf; ELETTRONICO

Σύνδεσμος πρόσβασης: https://zbmath.org/6867672
https://doi.org/10.1016/j.artint.2017.11.006
https://dblp.uni-trier.de/db/journals/ai/ai256.html#CimattiDMRS18
https://philpapers.org/rec/CIMSTP
https://cris.fbk.eu/handle/11582/312559
https://doi.org/10.1016/j.artint.2017.11.006
https://www.sciencedirect.com/science/article/pii/S0004370217301431
https://hdl.handle.net/11572/258649
http://www.sciencedirect.com/science/article/pii/S0004370217301431
https://doi.org/10.1016/j.artint.2017.11.006

Dependency structures for decision tables

Συγγραφείς: Tommaso Gentile, Giampiero Chiaselotti, Federico Infusino

Πηγή: International Journal of Approximate Reasoning. 88:333-370

Θεματικοί όροι: 0202 electrical engineering, electronic engineering, information engineering, 0102 computer and information sciences, 02 engineering and technology, Problem solving in the context of artificial intelligence (heuristics, search strategies, etc.), 16. Peace & justice, Reasoning under uncertainty in the context of artificial intelligence, 01 natural sciences

Περιγραφή αρχείου: application/xml

Σύνδεσμος πρόσβασης: https://www.sciencedirect.com/science/article/pii/S0888613X1730395X
https://iris.unical.it/handle/20.500.11770/156288
https://doi.org/10.1016/j.ijar.2017.06.007
https://dblp.uni-trier.de/db/journals/ijar/ijar88.html#ChiaselottiGI17

Optimal Mutation Rates for the (1+ $$\lambda $$ λ ) EA on OneMax Through Asymptotically Tight Drift Analysis: Optimal mutation rates for the \((1+\lambda)\) EA on OneMax through asymptotically tight drift analysis

Συγγραφείς: Gießen, Christian, Witt, Carsten

Πηγή: Gießen, C & Witt, C 2018, ' Optimal Mutation Rates for the (1+ λ) EA on OneMax Through Asymptotically Tight Drift Analysis ', Algorithmica, vol. 80, no. 5, pp. 1710-1731 . https://doi.org/10.1007/s00453-017-0360-y

Θεματικοί όροι: Populations, Randomized algorithms, 0102 computer and information sciences, 02 engineering and technology, populations, 16. Peace & justice, 01 natural sciences, Mutation, 0202 electrical engineering, electronic engineering, information engineering, Analysis of algorithms, Runtime analysis, mutation, Problem solving in the context of artificial intelligence (heuristics, search strategies, etc.), runtime analysis

Περιγραφή αρχείου: application/xml; application/pdf

Σύνδεσμος πρόσβασης: https://backend.orbit.dtu.dk/ws/files/198800127/mutationrates_rev2.pdf
https://zbmath.org/6870386
https://doi.org/10.1007/s00453-017-0360-y
https://link.springer.com/article/10.1007/s00453-017-0360-y
https://link.springer.com/content/pdf/10.1007%2Fs00453-017-0360-y.pdf
https://link.springer.com/article/10.1007/s00453-017-0360-y/fulltext.html
https://dblp.uni-trier.de/db/journals/algorithmica/algorithmica80.html#GiessenW18
https://orbit.dtu.dk/en/publications/d2b4e53f-fcb5-43d7-91d7-668e3160e07a

Static and Self-Adjusting Mutation Strengths for Multi-valued Decision Variables: Static and self-adjusting mutation strengths for multi-valued decision variables

Συγγραφείς: Doerr, Benjamin, Doerr, Carola, Kötzing, Timo

Συνεισφορές: Doerr, Carola, Laboratoire d'informatique de l'École polytechnique Palaiseau (LIX), École polytechnique (X), Institut Polytechnique de Paris (IP Paris)-Institut Polytechnique de Paris (IP Paris)-Centre National de la Recherche Scientifique (CNRS), Centre National de la Recherche Scientifique (CNRS), Recherche Opérationnelle (RO), LIP6, Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Friedrich-Schiller-Universität = Friedrich Schiller University Jena Jena, Germany

Πηγή: Algorithmica. 80:1732-1768

Θεματικοί όροι: parameter choice, [INFO.INFO-DS]Computer Science [cs]/Data Structures and Algorithms [cs.DS], Randomized algorithms, [INFO.INFO-NE] Computer Science [cs]/Neural and Evolutionary Computing [cs.NE], parameter control, [INFO.INFO-DS] Computer Science [cs]/Data Structures and Algorithms [cs.DS], 0102 computer and information sciences, 02 engineering and technology, [INFO.INFO-NE]Computer Science [cs]/Neural and Evolutionary Computing [cs.NE], Approximation methods and heuristics in mathematical programming, 01 natural sciences, theory of randomized search heuristics, genetic algorithms, 0202 electrical engineering, electronic engineering, information engineering, Analysis of algorithms, Problem solving in the context of artificial intelligence (heuristics, search strategies, etc.), runtime analysis

Περιγραφή αρχείου: application/xml

Σύνδεσμος πρόσβασης: https://zbmath.org/6870387
https://doi.org/10.1007/s00453-017-0341-1
https://dblp.uni-trier.de/db/journals/algorithmica/algorithmica80.html#DoerrDK18
https://hal.archives-ouvertes.fr/hal-01668260
https://link.springer.com/content/pdf/10.1007%2Fs00453-017-0341-1.pdf
https://link.springer.com/article/10.1007/s00453-017-0341-1
https://hal.science/hal-01668260v1
https://doi.org/10.1007/s00453-017-0341-1

The (1+ λ ) evolutionary algorithm with self-adjusting mutation rate: The \((1+\lambda)\) evolutionary algorithm with self-adjusting mutation rate

Συγγραφείς: Doerr, Benjamin, Gießen, Christian, Witt, Carsten, Yang, Jing

Πηγή: Doerr, B, Witt, C, Gießen, C & Yang, J 2017, The (1+λ) evolutionary algorithm with self-adjusting mutation rate . in Proceedings of 2017 Genetic and Evolutionary Computation Conference . Association for Computing Machinery, pp. 1351-1358, 2017 Genetic and Evolutionary Computation Conference, Berlin, Berlin, Germany, 15/07/2017 . https://doi.org/10.1145/3071178.3071279
Doerr, B, Gießen, C, Witt, C & Yang, J 2018, ' The (1 + λ) Evolutionary Algorithm with Self-Adjusting Mutation Rate ', Algorithmica, vol. 81, no. 2, pp. 593–631 . https://doi.org/10.1007/s00453-018-0502-x

Θεματικοί όροι: Optimization, FOS: Computer and information sciences, Optimization Techniques, Black box algorithms, Evolutionary computation, 0102 computer and information sciences, 02 engineering and technology, Evolutionary algorithms, Adjustment mechanisms, 01 natural sciences, self-adaptation, 0202 electrical engineering, electronic engineering, information engineering, Analysis of algorithms, Neural and Evolutionary Computing (cs.NE), Self-adaptation, Run-time analysis, runtime analysis, Computer Science - Neural and Evolutionary Computing, Dynamic parameter control, Current mutations, Approximation methods and heuristics in mathematical programming, evolutionary computation, Mutation, Expected optimization time, Runtime analysis, mutation, Fitness evaluations, Problem solving in the context of artificial intelligence (heuristics, search strategies, etc.)

Περιγραφή αρχείου: application/xml; application/pdf

Σύνδεσμος πρόσβασης: http://arxiv.org/pdf/1704.02191
http://arxiv.org/abs/1704.02191
https://www.arxiv.org/abs/1704.02191
https://ui.adsabs.harvard.edu/abs/2017arXiv170402191D/abstract
https://dblp.uni-trier.de/db/journals/corr/corr1704.html#DoerrGWY17
https://dl.acm.org/doi/10.1145/3071178.3071279
https://orbit.dtu.dk/en/publications/the-1-evolutionary-algorithm-with-selfadjusting-mutation-rate(68f9836c-c58d-48e5-bd9a-07dd3eadfa4d).html
https://orbit.dtu.dk/files/134976547/1704.02191.pdf
http://dblp.uni-trier.de/db/conf/gecco/gecco2017.html#DoerrGWY17
https://arxiv.org/pdf/1704.02191.pdf
https://orbit.dtu.dk/en/publications/68f9836c-c58d-48e5-bd9a-07dd3eadfa4d
https://orbit.dtu.dk/en/publications/9da771a6-2ba8-4331-992a-7bb724df2a6f