Arina Buzdalova

Publication Activity (10 Years)

Years Active: 2012-2022
Publications (10 Years): 23

Top Topics

Population Size

Evolutionary Algorithm

Reinforcement Learning

Top Venues

GECCO (Companion)

Publications

Nina Bulanova, Arina Buzdalova, Carola Doerr
Fast Re-Optimization of LeadingOnes with Frequent Changes. CEC (2022)
Nina Bulanova, Arina Buzdalova, Carola Doerr
Fast Re-Optimization of LeadingOnes with Frequent Changes. CoRR (2022)
Kirill Antonov, Maxim Buzdalov, Arina Buzdalova, Carola Doerr
Blending Dynamic Programming with Monte Carlo Simulation for Bounding the Running Time of Evolutionary Algorithms. CEC (2021)
Kirill Antonov, Maxim Buzdalov, Arina Buzdalova, Carola Doerr
Blending Dynamic Programming with Monte Carlo Simulation for Bounding the Running Time of Evolutionary Algorithms. CoRR (2021)
Arina Buzdalova, Carola Doerr, Anna Rodionova
Hybridizing the 1/5-th Success Rule with Q-Learning for Controlling the Mutation Rate of an Evolutionary Algorithm. PPSN (2) (2020)
Arina Buzdalova, Carola Doerr, Anna Rodionova
Hybridizing the 1/5-th Success Rule with Q-Learning for Controlling the Mutation Rate of an Evolutionary Algorithm. CoRR (2020)
Ivan Ignashov, Arina Buzdalova, Maxim Buzdalov, Carola Doerr
Illustrating the trade-off between time, quality, and success probability in heuristic search: a discussion paper. GECCO (Companion) (2019)
Anna Rodionova, Kirill Antonov, Arina Buzdalova, Carola Doerr
Offspring Population Size Matters when Comparing Evolutionary Algorithms with Self-Adjusting Mutation Rates. CoRR (2019)
Anna Rodionova, Kirill Antonov, Arina Buzdalova, Carola Doerr
Offspring population size matters when comparing evolutionary algorithms with self-adjusting mutation rates. GECCO (2019)
Dmitry Vinokurov, Maxim Buzdalov, Arina Buzdalova, Benjamin Doerr, Carola Doerr
Fixed-target runtime analysis of the (1 + 1) EA with resampling. GECCO (Companion) (2019)
Denis Antipov, Arina Buzdalova, Andrew Stankevich
Runtime analysis of a population-based evolutionary algorithm with auxiliary objectives selected by reinforcement learning. GECCO (Companion) (2018)
Irina Petrova, Arina Buzdalova
Reinforcement learning based dynamic selection of auxiliary objectives with preservation of the best found solution. GECCO (Companion) (2017)
Denis Antipov, Arina Buzdalova
Runtime Analysis of Random Local Search on JUMP function with Reinforcement Based Selection of Auxiliary Objectives. CEC (2017)
Anton O. Bassin, Arina Buzdalova
Selection of Auxiliary Objectives Using Landscape Features and Offline Learned Classifier. EvoCOP (2017)
Irina Petrova, Arina Buzdalova
Reinforcement Learning Based Dynamic Selection of Auxiliary Objectives with Preserving of the Best Found Solution. CoRR (2017)
Arina Buzdalova, Irina Petrova, Maxim Buzdalov
Runtime analysis of different Approaches to select conflicting auxiliary objectives in the generalized OneMax problem. SSCI (2016)
Arkady Rost, Irina Petrova, Arina Buzdalova
Adaptive Parameter Selection in Evolutionary Algorithms by Reinforcement Learning with Dynamic Discretization of Parameter Range. GECCO (Companion) (2016)
Arkady Rost, Irina Petrova, Arina Buzdalova
Adaptive Parameter Selection in Evolutionary Algorithms by Reinforcement Learning with Dynamic Discretization of Parameter Range. CoRR (2016)
Nina Bulanova, Arina Buzdalova, Maxim Buzdalov
Fitness-Dependent Hybridization of Clonal Selection Algorithm and Random Local Search. GECCO (Companion) (2016)
Maxim Buzdalov, Arina Buzdalova
Can OneMax help optimizing LeadingOnes using the EA+RL method? CEC (2015)
Arina Buzdalova, Anna Matveeva, Georgiy Korneev
Selection of Auxiliary Objectives with Multi-Objective Reinforcement Learning. GECCO (Companion) (2015)
Irina Petrova, Arina Buzdalova
Selection of Auxiliary Objectives in the Travelling Salesman Problem using Reinforcement Learning. GECCO (Companion) (2015)
Maxim Buzdalov, Arina Buzdalova
Analysis of Q-learning with random exploration for selection of auxiliary objectives in random local search. CEC (2015)
Maxim Buzdalov, Arina Buzdalova
Onemax helps optimizing XdivK: : theoretical runtime analysis for RLS and EA+RL. GECCO (Companion) (2014)
Irina Petrova, Arina Buzdalova, Maxim Buzdalov
Improved Selection of Auxiliary Objectives Using Reinforcement Learning in Non-stationary Environment. ICMLA (2014)
Arina Buzdalova, Vladislav Kononov, Maxim Buzdalov
Selecting evolutionary operators using reinforcement learning: initial explorations. GECCO (Companion) (2014)
Maxim Buzdalov, Irina Petrova, Arina Buzdalova
NSGA-II implementation details may influence quality of solutions for the job-shop scheduling problem. GECCO (Companion) (2014)
Arina Buzdalova, Maxim Buzdalov
A New Algorithm for Adaptive Online Selection of Auxiliary Objectives. ICMLA (2014)
Maxim Buzdalov, Arina Buzdalova, Irina Petrova
Generation of tests for programming challenge tasks using multi-objective optimization. GECCO (Companion) (2013)
Irina Petrova, Arina Buzdalova, Maxim Buzdalov
Improved Helper-Objective Optimization Strategy for Job-Shop Scheduling Problem. ICMLA (2) (2013)
Maxim Buzdalov, Arina Buzdalova
Adaptive selection of helper-objectives for test case generation. IEEE Congress on Evolutionary Computation (2013)
Maxim Buzdalov, Arina Buzdalova, Anatoly Shalyto
A First Step towards the Runtime Analysis of Evolutionary Algorithm Adjusted with Reinforcement Learning. ICMLA (1) (2013)
Arina Buzdalova, Maxim Buzdalov, Vladimir Parfenov
Generation of Tests for Programming Challenge Tasks Using Helper-Objectives. SSBSE (2013)
Arina Buzdalova, Maxim Buzdalov
Increasing Efficiency of Evolutionary Algorithms by Choosing between Auxiliary Fitness Functions with Reinforcement Learning. ICMLA (1) (2012)
Arina Buzdalova, Maxim Buzdalov
Adaptive Selection of Helper-Objectives with Reinforcement Learning. ICMLA (2) (2012)