Научные руководители
Буздалов Максим Викторовичкандидат технических наук mbuzdalov@itmo.ru Структурное подразделение: факультет информационных технологий и программирования Должность: программист Профиль: 05.13.11 - Математическое и программное обеспечение вычислительных машин, комплексов и компьютерных сетей 05.13.17 - Теоретические основы информатики Область интересов: Эволюционные вычисления. Машинное обучение. Теоретическая информатика. Алгоритмы и структуры данных. Рабочий язык: Английский, Русский |
Публикации руководителя
| Выходные данные | Год | Индексирование в БД |
| Bassin A., Buzdalov M. An Experimental Study of Operator Choices in the (1 + (lambda, lambda)) Genetic Algorithm//Communications in Computer and Information Science, 2020, Vol. 1275, pp. 320–335 | 2020 | Scopus, Web of Science |
| Antipov D., Buzdalov M., Doerr B. First Steps Towards a Runtime Analysis When Starting With a Good Solution//Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2020, Vol. 12270 LNCS, pp. 560-573 | 2020 | Scopus, Web of Science |
| Mishra S., Buzdalov M. If unsure, shuffle: Deductive sort is Theta(MN3), but O(MN2) in expectation over input permutations//GECCO 2020 - Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2020, pp. 516-523 | 2020 | Scopus, Web of Science |
| Buzdalov M., Doerr B., Doerr C., Vinokurov D. Fixed-Target Runtime Analysis//GECCO 2020 - Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2020, pp. 1295-1303 | 2020 | Scopus, Web of Science |
| Bassin A., Buzdalov M. The (1+(lambda,lambda)) Genetic Algorithm for Permutations//GECCO 2020 - Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2020, pp. 1669-1677 | 2020 | Scopus, Web of Science |
| Buzdalov M., Doerr C. Optimal Mutation Rates for the (1+ lambda) EA on OneMax//Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2020, Vol. 12270 LNCS, pp. 574-587 | 2020 | Scopus, Web of Science |
| Mishra S., Buzdalov M. Filter Sort is Omega(N3) in the Worst Case//Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2020, Vol. 12270 LNCS, pp. 675-685 | 2020 | Scopus, Web of Science |
| Buzdalov M., Kolyubin S., Egorov A.A., Borisov I.I. Optimizing Robotic Cheetah Leg Parameters using Evolutionary Algorithms//Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2020, Vol. 12438 LNCS, pp. 214-227 | 2020 | Scopus, Web of Science |
| Mishra S., Buzdalov M., Senwar R. Time Complexity Analysis of the Dominance Degree Approach for Non-Dominated Sorting//GECCO 2020 - Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2020, pp. 169-170 | 2020 | Scopus, Web of Science |
| Antipov D., Buzdalov M., Doerr B. Fast Mutation in Crossover-based Algorithms//GECCO 2020 - Proceedings of the Genetic and Evolutionary Computation Conference Companion, 2020, pp. 1268-1276 | 2020 | Scopus, Web of Science |
| Басин А., Буздалов М.В. Адаптация размера популяции в (1+(lambda,lambda))~ГА при помощи модифицированного правила одной пятой // СПИСОК-2019 Материалы всероссийской научной конференции по проблемам информатики (СПб, 23-26апреля 2019г.) -2019. - С. 202-208 | 2019 | |
| Ignashov I., Buzdalov M., Buzdalova A., Doerr C. Illustrating the trade-off between time, quality, and success probability in heuristic search//GECCO 2019 - Proceedings of the 2019 Genetic and Evolutionary Computation Conference Companion, 2019, pp. 1807-1812 | 2019 | Scopus, Web of Science |
| Buzdalov M. Generalized incremental orthant search: Towards efficient steady-state evolutionary multiobjective algorithms//GECCO 2019 - Proceedings of the 2019 Genetic and Evolutionary Computation Conference Companion, 2019, pp. 1357-1365 | 2019 | Scopus, Web of Science |
| Buzdalov M. Towards better estimation of statistical significance when comparing evolutionary algorithms//GECCO 2019 - Proceedings of the 2019 Genetic and Evolutionary Computation Conference Companion, 2019, pp. 1782-1788 | 2019 | Scopus, Web of Science |
| Pavlenko A., Buzdalov M., Ulyantsev V. Fitness Comparison by Statistical Testing in Construction of SAT-Based Guess-and-Determine Cryptographic Attacks//GECCO 2019 - Proceedings of the 2019 Genetic and Evolutionary Computation Conference Companion, 2019, pp. 312-320 | 2019 | Scopus, Web of Science |
| Bassin A., Buzdalov M. The 1/5-th Rule with Rollbacks: On Self-Adjustment of the Population Size in the (1+(lambda,lambda))GA//GECCO 2019 - Proceedings of the 2019 Genetic and Evolutionary Computation Conference Companion, 2019, pp. 277-278 | 2019 | Scopus, Web of Science |
| Bulanova N., Buzdalov M. Limited Memory, Limited Arity Unbiased Black-Box Complexity: First Insights//GECCO 2019 - Proceedings of the 2019 Genetic and Evolutionary Computation Conference Companion, 2019, pp. 2020-2023 | 2019 | Scopus, Web of Science |
| Bulanova N., Buzdalov M. Black-Box Complexity of the Binary Value Function//GECCO 2019 - Proceedings of the 2019 Genetic and Evolutionary Computation Conference Companion, 2019, pp. 423-424 | 2019 | Scopus, Web of Science |
| Vinokurov D., Buzdalov M., Buzdalova A., Doerr B., Doerr C. Fixed-Target Runtime Analysis of the (1 + 1) EA with Resampling//GECCO 2019 - Proceedings of the 2019 Genetic and Evolutionary Computation Conference Companion, 2019, pp. 2068-2071 | 2019 | Scopus, Web of Science |
| Buzdalov M. Make Evolutionary Multiobjective Algorithms Scale Better with Advanced Data Structures: Van Emde Boas Tree for Non-Dominated Sorting//Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2019, Vol. 11411, pp. 66-77 | 2019 | Scopus, Web of Science |
| Mironovich V., Buzdalov M., Vyatkin V.V. Permutation Encoding for Automatic Reconstruction of Connections in Closed-Loop Control System using Evolutionary Algorithm//24th IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2019, 2019, pp. 1265-1268 | 2019 | Scopus, Web of Science |
| Bulanova N., Buzdalov M. Better Fixed-Arity Unbiased Black-Box Algorithms//GECCO 2018 Companion - Proceedings of the 2018 Genetic and Evolutionary Computation Conference Companion, 2018, pp. 322-323 | 2018 | Scopus |
| Mironovich V., Buzdalov M., Vyatkin V. Automatic Plant-Controller Input/Output Matching using Evolutionary Algorithms//Proceedings of the 23rd IEEE International Conference on Emerging Technologies and Factory Automation (EFTA), 2018, pp. 1043-1046 | 2018 | Scopus, Web of Science |
| Markina M., Buzdalov M. Towards Large-Scale Multiobjective Optimisation with a Hybrid Algorithm for Non-Dominated Sorting//Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2018, Vol. 11101, pp. 347-358 | 2018 | Scopus, Web of Science |
| Yakupov I., Buzdalov M. On Asynchronous Non-Dominated Sorting for Steady-State Multiobjective Evolutionary Algorithms//GECCO 2018 Companion - Proceedings of the 2018 Genetic and Evolutionary Computation Conference Companion, 2018, pp. 205-206 | 2018 | Scopus |
| Buzdalov M. Generalized Offline Orthant Search: One Code for Many Problems in Multiobjective Optimization//GECCO 2018 Companion - Proceedings of the 2018 Genetic and Evolutionary Computation Conference Companion, 2018, pp. 593-600 | 2018 | Scopus |
| Mironovich V., Buzdalov M., Vyatkin V. From Fitness Landscape Analysis to Designing Evolutionary Algorithms: The Case Study in Automatic Generation of Function Block Applications//GECCO 2018 Companion - Proceedings of the 2018 Genetic and Evolutionary Computation Conference Companion, 2018, pp. 1902-1905 | 2018 | Scopus |
| Mironovich V., Buzdalov M. Evaluation of Heavy-tailed Mutation Operator on Maximum Flow Test Generation Problem//GECCO 2017 - Proceedings of the Genetic and Evolutionary Computation Conference, 2017, pp. 1423-1426 | 2017 | Scopus, Web of Science |
| Mironovich V., Buzdalov M., Vyatkin V. Automatic Generation of Function Block Applications Using Evolutionary Algorithms: Initial Explorations//Proceedings of 2017 15th IEEE International Conference on Industrial Informatics (INDIN), 2017, pp. 700-705 | 2017 | Scopus, Web of Science |
| Yakupov I., Buzdalov M. Improved Incremental Non-dominated Sorting for Steady-State Evolutionary Multiobjective Optimization//GECCO 2017 - Proceedings of the Genetic and Evolutionary Computation Conference, 2017, pp. 649-656 | 2017 | Scopus, Web of Science |
| Buzdalov M., Doerr B. Runtime Analysis of the (1 + (lambda, lambda)) Genetic Algorithm on Random Satisfiable 3-CNF Formulas//GECCO 2017 - Proceedings of the Genetic and Evolutionary Computation Conference, 2017, pp. 1343-1350 | 2017 | Scopus, Web of Science |
| Миронович В.А., Буздалов М.В. Выбор функции приспособленности для автоматической генерации связей данных в программах из функциональных блоков // СПИСОК-2017 Материалы всероссийской научной конференции по проблемам информатики (СПб, 25-27апреля 2017г.) -2017. - С. 319-325 | 2017 | |
| Антипов Д.С., Буздалов М.В. Поиск оптимальной вероятности мутации для решения задачи XdivK // СПИСОК-2017 Материалы всероссийской научной конференции по проблемам информатики (СПб, 25-27апреля 2017г.) -2017. - С. 291-295 | 2017 | |
| Markina M., Buzdalov M. Hybridizing Non-dominated Sorting Algorithms: Divide-and-Conquer Meets Best Order Sort//GECCO 2017 - Proceedings of the Genetic and Evolutionary Computation Conference, 2017, pp. 153-154 | 2017 | Scopus, Web of Science |
| Bulanova N., Buzdalov M. On Binary Unbiased Operators Returning Multiple Offspring//GECCO 2017 - Proceedings of the Genetic and Evolutionary Computation Conference, 2017, pp. 1395-1398 | 2017 | Scopus, Web of Science |
| Буздалова А.С., Петрова И.А., Буздалов М.В. Анализ времени работы методов выбора вспомогательных критериев оптимизации на обобщенной задаче OneMax // СПИСОК-2016 Материалы всероссийской научной конференции по проблемам информатики (СПб, 26-29 апреля 2016г.) -2016. - С. 282-287 | 2016 | |
| Миронович В.А., Буздалов М.В. Генерация тестов для задачи поиска максимального потока с использованием эволюционных алгоритмов и матричного представления графа // СПИСОК-2016 Материалы всероссийской научной конференции по проблемам информатики (СПб, 26-29 апреля 2016г.) -2016. - С. 275-282 | 2016 | |
| Антипов Д.С., Буздалов М.В. Теоретический анализ времени работы эволюционных алгоритмов при генерации тестов // СПИСОК-2016 Материалы всероссийской научной конференции по проблемам информатики (СПб, 26-29 апреля 2016г.) -2016. - С. 298-303 | 2016 | |
| Буланова Н.С., Буздалова А.С., Буздалов М.В. Гибридизация искусственных иммунных систем и эволюционных алгоритмов // СПИСОК-2016 Материалы всероссийской научной конференции по проблемам информатики (СПб, 26-29 апреля 2016г.) -2016. - С. 262-267 | 2016 | |
| Polevaya T., Buzdalov M. Preserving diversity in auxiliary objectives provably speeds up crossing plateaus//IEEE Symposium Series on Computational Intelligence, SSCI 2016, 2016, pp. 7850145 | 2016 | Scopus, Web of Science |
| Antipov D., Buzdalov M., Korneev G. First Steps in Runtime Analysis of Worst-Case Execution Time Test Generation for the Dijkstra Algorithm using an Evolutionary Algorithm//Mendel, 2016, pp. 43-48 | 2016 | Scopus |
| Buzdalov M., Doerr B., Kever M. The Unrestricted Black-Box Complexity of Jump Functions//Evolutionary Computation, 2016, Vol. 24, No. 4, pp. 719-744 | 2016 | Scopus, Web of Science |
| Nigmatullin N., Buzdalov M., Stankevich A. Efficient removal of points with smallest crowding distance in two-dimensional incremental non-dominated sorting//GECCO 2016 - Proceedings of the 2016 Genetic and Evolutionary Computation Conference, 2016, pp. 1121-1128 | 2016 | Scopus, Web of Science |
| Buzdalova A., Petrova I., Buzdalov M. Runtime Analysis of Different Approaches to Select Conflicting Auxiliary Objectives in the Generalized OneMax Problem//IEEE Symposium Series on Computational Intelligence, SSCI 2016, 2016, pp. 280-286 | 2016 | Scopus, Web of Science |
| Mironovich V., Buzdalov M., Parfenov V. Comparative Study of Representations in the Maximum Flow Test Generation Problem//Mendel, 2016, pp. 67-72 | 2016 | Scopus |
| Vasin A., Buzdalov M. A Faster Algorithm for the Binary Epsilon Indicator Based on Orthant Minimum Search//GECCO 2016 - Proceedings of the 2016 Genetic and Evolutionary Computation Conference, 2016, pp. 613-620 | 2016 | Scopus, Web of Science |
| Buzdalov M. An Algorithm for Computing Lower Bounds for Unrestricted Black-Box Complexities//GECCO 2016 - Proceedings of the 2016 Genetic and Evolutionary Computation Conference, 2016, pp. 147-148 | 2016 | Scopus, Web of Science |
| Bulanova N., Buzdalova A., Buzdalov M. Fitness-Dependent Hybridization of Clonal Selection Algorithm and Random Local Search//GECCO 2016 - Proceedings of the 2016 Genetic and Evolutionary Computation Conference, 2016, pp. 5-6 | 2016 | Scopus, Web of Science |
| Yakupov I., Buzdalov M. Incremental Non-Dominated Sorting with O(N) Insertion for the Two-Dimensional Case//IEEE Congress on Evolutionary Computation, CEC 2015 - Proceedings, 2015, pp. 1853-1860 | 2015 | Scopus, Web of Science |
| Antipov D.S., Buzdalov M.V., Doerr B. Runtime Analysis of (1+1) Evolutionary Algorithm Controlled with Q-learning using Greedy Exploration Strategy on OneMax+ZeroMax Problem//Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2015, Vol. 9026, pp. 160-172 | 2015 | Scopus, Web of Science |
| Buzdalov M.V., Kever M.E., Doerr B. Upper and Lower Bounds on Unrestricted Black-Box Complexity of Jump(n,l)//Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2015, Vol. 9026, pp. 209-221 | 2015 | Scopus, Web of Science |
| Buzdalov M., Shalyto A. Hard Test Generation for Augmenting Path Maximum Flow Algorithms using Genetic Algorithms: Revisited//IEEE Congress on Evolutionary Computation, CEC 2015 - Proceedings, 2015, pp. 2121-2128 | 2015 | Scopus, Web of Science |
| Buzdalov M., Buzdalova A. Can OneMax Help Optimizing LeadingOnes using the EA+RL Method?//IEEE Congress on Evolutionary Computation, CEC 2015 - Proceedings, 2015, pp. 1762-1768 | 2015 | Scopus, Web of Science |
| Buzdalov M., Buzdalova A. Analysis of Q-Learning with Random Exploration for Selection of Auxiliary Objectives in Random Local Search//IEEE Congress on Evolutionary Computation, CEC 2015 - Proceedings, 2015, pp. 1776-1783 | 2015 | Scopus, Web of Science |
| Arkhipov V., Buzdalov M. An asynchronous implementation of the limited memory CMA-ES: First results//Mendel, 2015, pp. 43-46 | 2015 | Scopus |
| Buzdalov M., Yakupov I., Stankevich A. Fast Implementation of the Steady-State NSGA-II Algorithm for Two Dimensions Based on Incremental Non-Dominated Sorting//GECCO'15: Proceedings of the 2015 Genetic and Evolutionary Computation Conference, 2015, pp. 647-654 | 2015 | Scopus, Web of Science |
| Buzdalov M., Parfenov V. Various Degrees of Steadiness in NSGA-II and Their Influence on the Quality of Results//GECCO'15: Proceedings of the 2015 Genetic and Evolutionary Computation Conference, 2015, pp. 749-750 | 2015 | Scopus, Web of Science |
| Mironovich V., Buzdalov M. Hard Test Generation for Maximum Flow Algorithms with the Fast Crossover-Based Evolutionary Algorithm//GECCO'15: Proceedings of the 2015 Genetic and Evolutionary Computation Conference, 2015, pp. 1229-1232 | 2015 | Scopus, Web of Science |
| Arkhipov V.V., Buzdalov M.V., Shalyto A.A. An asynchronous implementation of the limited memory CMA-ES//14th International Conference on Machine Learning and Applications, ICMLA 2015, 2015, pp. 707-712 | 2015 | Scopus, Web of Science |
| Mironovich V., Buzdalov M. Generation of tests against a greedy algorithm for the knapsack problem using an evolutionary algorithm//Mendel, 2014, pp. 77-82 | 2014 | Scopus |
| Buzdalov M. A Switch-and-Restart Algorithm with Exponential Restart Strategy for Objective Selection and its Runtime Analysis//Proceedings - 2014 13th International Conference on Machine Learning and Applications, ICMLA 2014, 2014, pp. 141-146 | 2014 | Scopus, Web of Science |
| Petrova I., Buzdalova A., Buzdalov M. Improved Selection of Auxiliary Objectives using Reinforcement Learning in Non-Stationary Environment//Proceedings - 2014 13th International Conference on Machine Learning and Applications, ICMLA 2014, 2014, pp. 580-583 | 2014 | Scopus, Web of Science |
| Buzdalova A., Buzdalov M. A New Algorithm for Adaptive Online Selection of Auxiliary Objectives//Proceedings - 2014 13th International Conference on Machine Learning and Applications, ICMLA 2014, 2014, pp. 584-587 | 2014 | Scopus, Web of Science |
| Buzdalov M., Shalyto A. Worst-Case Execution Time Test Generation for Solutions of the Knapsack Problem Using a Genetic Algorithm//Communications in Computer and Information Science, 2014, Vol. 472, pp. 1-10 | 2014 | Scopus, Web of Science |
| Lukin M., Buzdalov M., Shalyto A. Formal Verification of 800 Genetically Constructed Automata Programs: A Case Study//Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2014, Vol. 8855, pp. 165-170 | 2014 | Scopus |
| Buzdalov M., Shalyto A. A Provably Asymptotically Fast Version of the Generalized Jensen Algorithm for Non-Dominated Sorting//Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2014, Vol. 8672, pp. 528-537 | 2014 | Scopus, Web of Science |
| Buzdalov M., Knyazev S., Porozov Y. Protein Conformation Motion Modeling using sep-CMA-ES//Proceedings - 2014 13th International Conference on Machine Learning and Applications, ICMLA 2014, 2014, pp. 35-40 | 2014 | Scopus, Web of Science |
| Buzdalov M., Petrova I., Buzdalova A. NSGA-II Implementation Details May Influence Quality of Solutions for the Job-Shop Scheduling Problem//GECCO 2014 - Companion Publication of the 2014 Genetic and Evolutionary Computation Conference, 2014, pp. 1445-1446 | 2014 | Scopus |
| Petrova I., Buzdalova A., Buzdalov M. Selection of Extra Objectives using Reinforcement Learning in Non-Stationary Environment: Initial Explorations//Mendel, 2014, pp. 105-110 | 2014 | Scopus |
| Kravtsov N., Buzdalov M., Buzdalova A., Shalyto A. Worst-Case Execution Time Test Generation using Genetic Algorithms with Automated Construction and Online Selection of Objectives//Mendel, 2014, pp. 111-116 | 2014 | Scopus |
| Buzdalov M., Buzdalova A. OneMax helps optimizing XdivK: Theoretical runtime analysis for RLS and EA+RL//GECCO 2014 - Companion Publication of the 2014 Genetic and Evolutionary Computation Conference, 2014, pp. 201-202 | 2014 | Scopus |
| Buzdalova A., Kononov V., Buzdalov M. Selecting Evolutionary Operators using Reinforcement Learning: Initial Explorations//GECCO 2014 - Companion Publication of the 2014 Genetic and Evolutionary Computation Conference, 2014, pp. 1033-1036 | 2014 | Scopus |
| Buzdalov M.V., Tcarev F.N. An evolutionary approach to hard test case generation for shortest common superstring problem//Proceedings - 1st BRICS Countries Congress on Computational Intelligence, BRICS-CCI 2013, 2013, pp. 81-85 | 2013 | Scopus, Web of Science |
| Buzdalova A.S., Buzdalov M.V., Parfenov V.G. Generation of tests for programming challenge tasks using helper-objectives//Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2013, Vol. 8084, No. LNCS, pp. 300-305 | 2013 | Scopus |
| Спельников Д.М., Князев С.Н., Балахонцева М.А., Буздалов М.В., Порозов Ю.Б., Маслов В.Г., Бухановский А.В. Высокопроизводительный программный комплекс моделирования конформационно-зависимых свойств белков в задачах рационального дизайна лекарственных препаратов // Динамика сложных систем - XXI век -2013. - Т. 7. - № 3. - С. 12-16 | 2013 | ВАК, РИНЦ |
| Buzdalov M., Buzdalova A., Shalyto A. A First Step towards the Runtime Analysis of Evolutionary Algorithm Adjusted with Reinforcement Learning//Proceedings - 2013 12th International Conference on Machine Learning and Applications, ICMLA 2013, 2013, Vol. 1, pp. 203-208 | 2013 | Scopus, Web of Science |
| Buzdalov M.V., Buzdalova A.S., Petrova I.A. Generation of tests for programming challenge tasks using multi-objective optimization//GECCO 2013 - Proceedings of the 2013 Genetic and Evolutionary Computation Conference, 2013, pp. 1655-1658 | 2013 | Scopus, Web of Science |
| Arkhipov V., Buzdalov M., Shalyto A. Worst-Case Execution Time Test Generation for Augmenting Path Maximum Flow Algorithms using Genetic Algorithms//Proceedings - 2013 12th International Conference on Machine Learning and Applications, ICMLA 2013, 2013, Vol. 2, pp. 108-111 | 2013 | Scopus, Web of Science |
| Petrova I., Buzdalova A., Buzdalov M. Improved Helper-Objective Optimization Strategy for Job-Shop Scheduling Problem//Proceedings - 2013 12th International Conference on Machine Learning and Applications, ICMLA 2013, 2013, Vol. 2, pp. 374-377 | 2013 | Scopus, Web of Science |
| Buzdalov M., Buzdalova A. Adaptive selection of helper-objectives for test case generation//2013 IEEE Congress on Evolutionary Computation, CEC 2013, 2013, pp. 2245-2250 | 2013 | Scopus, Web of Science |
| Афанасьева А.С., Буздалов М.В. Выбор функции приспособленности особей генетического алгоритма с помощью обучения с подкреплением // Научно-технический вестник информационных технологий, механики и оптики [Scientific and Technical Journal of Information Technologies, Mechanics and Optics] -2012. - № 1(77). - С. 77-81 | 2012 | ВАК, РИНЦ |
| Buzdalov M. Generation of tests for programming challenge tasks on graph theory using evolution strategy//Proceedings - 2012 11th International Conference on Machine Learning and Applications, ICMLA 2012, 2012, Vol. 2, pp. 62-65 | 2012 | Scopus |
| Buzdalova A., Buzdalov M. Increasing Efficiency of Evolutionary Algorithms by Choosing between Auxiliary Fitness Functions with Reinforcement Learning//Proceedings - 2012 11th International Conference on Machine Learning and Applications, ICMLA 2012, 2012, Vol. 1, pp. 150-155 | 2012 | Scopus |
| Buzdalova A., Buzdalov M. Adaptive Selection of Helper-Objectives with Reinforcement Learning//Proceedings - 2012 11th International Conference on Machine Learning and Applications, ICMLA 2012, 2012, Vol. 2, pp. 66-67 | 2012 | Scopus |
| Буздалова А.С., Буздалов М.В. Метод повышения эффективности эволюционных алгоритмов с помощью обучения с подкреплением // Научно-технический вестник информационных технологий, механики и оптики [Scientific and Technical Journal of Information Technologies, Mechanics and Optics] -2012. - № 5(81). - С. 115-119 | 2012 | ВАК, РИНЦ |
| Buzdalov M., Sokolov A.A. Evolving EFSMs solving a path-planning problem by genetic programming//GECCO 2012 Proceedings of the 14th annual conference companion on Genetic and evolutionary computation, 2012, pp. 591-594 | 2012 | Scopus, Web of Science |
| Afanasyeva A., Buzdalov M. Optimization with Auxiliary Criteria using Evolutionary Algorithms and Reinforcement Learning//Mendel, 2012, pp. 58-63 | 2012 | Scopus |
| Buzdalov M. Generation of tests for programming challenge tasks using evolution algorithms//Genetic and Evolutionary Computation Conference, GECCO'11 - Companion Publication, 2011, pp. 763-766 | 2011 | Scopus |
| Afanasyeva A., Buzdalov M. Choosing Best Fitness Function with Reinforcement Learning//Proceedings - 10th International Conference on Machine Learning and Applications, ICMLA 2011, 2011, Vol. 2, pp. 354-357 | 2011 | Scopus |