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ORCIDMadalina M. Drugan
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2010 – 2019
- 2019
[j13]Madalina M. Drugan:
Estimating the number of basins of attraction of multi-objective combinatorial problems. J. Comb. Optim. 37(4): 1367-1407 (2019)- [j12]Madalina M. Drugan
:
Random walk's correlation function for multi-objective NK landscapes and quadratic assignment problem. J. Comb. Optim. 38(4): 1213-1262 (2019) - [j11]Madalina M. Drugan:
Reinforcement learning versus evolutionary computation: A survey on hybrid algorithms. Swarm Evol. Comput. 44: 228-246 (2019) - [j10]Madalina M. Drugan:
Covariance Matrix Adaptation for Multiobjective Multiarmed Bandits. IEEE Trans. Neural Networks Learn. Syst. 30(8): 2493-2502 (2019) - [c50]Nil Stolt Ansó, Anton Orell Wiehe, Madalina M. Drugan, Marco A. Wiering:
Deep Reinforcement Learning for Pellet Eating in Agar.io. ICAART (2) 2019: 123-133 - 2018
- [j9]Madalina M. Drugan:
Scaling-up many-objective combinatorial optimization with Cartesian products of scalarization functions. J. Heuristics 24(2): 135-172 (2018) - [c49]Stefan J. L. Knegt, Madalina M. Drugan, Marco A. Wiering:
Opponent Modelling in the Game of Tron using Reinforcement Learning. ICAART (2) 2018: 29-40 - [c48]Stefan J. L. Knegt, Madalina M. Drugan, Marco A. Wiering:
Learning from Monte Carlo Rollouts with Opponent Models for Playing Tron. ICAART (Revised Selected Papers) 2018: 105-129 - [c47]Joseph Groot Kormelink, Madalina M. Drugan, Marco A. Wiering:
Exploration Methods for Connectionist Q-learning in Bomberman. ICAART (2) 2018: 355-362 - [c46]Remi Niel, Jasper Krebbers, Madalina M. Drugan, Marco A. Wiering:
Hierarchical Reinforcement Learning for Real-Time Strategy Games. ICAART (2) 2018: 470-477 - [c45]Jits Schilperoort, Ivar Mak, Madalina M. Drugan, Marco A. Wiering:
Learning to Play Pac-Xon with Q-Learning and Two Double Q-Learning Variants. SSCI 2018: 1151-1158 - [i1]Anton Orell Wiehe, Nil Stolt Ansó, Madalina M. Drugan, Marco A. Wiering:
Sampled Policy Gradient for Learning to Play the Game Agar.io. CoRR abs/1809.05763 (2018) - 2017
- [j8]Madalina M. Drugan, Marco A. Wiering, Peter Vamplew, Madhu Chetty:
Special issue on multi-objective reinforcement learning. Neurocomputing 263: 1-2 (2017) - [c44]Madalina M. Drugan:
PAC models in stochastic multi-objective multi-armed bandits. GECCO 2017: 409-416 - [c43]Richard Elderman, Leon J. J. Pater, Albert S. Thie, Madalina M. Drugan, Marco A. Wiering:
Adversarial Reinforcement Learning in a Cyber Security Simulation. ICAART (2) 2017: 559-566 - 2016
- [c42]Peter Auer, Chao-Kai Chiang, Ronald Ortner, Madalina M. Drugan:
Pareto Front Identification from Stochastic Bandit Feedback. AISTATS 2016: 939-947 - [c41]Madalina M. Drugan:
A Bayesian model for anomaly detection in SQL databases for security systems. SSCI 2016: 1-8 - [c40]Arryon D. Tijsma, Madalina M. Drugan, Marco A. Wiering:
Comparing exploration strategies for Q-learning in random stochastic mazes. SSCI 2016: 1-8 - 2015
- [j7]Madalina M. Drugan:
Generating QAP instances with known optimum solution and additively decomposable cost function. J. Comb. Optim. 30(4): 1138-1172 (2015) - [j6]Saba Q. Yahyaa, Madalina M. Drugan, Bernard Manderick:
Scalarized and Pareto Knowledge Gradient for Multi-objective Multi-armed Bandits. Trans. Comput. Collect. Intell. 20: 99-116 (2015) - [c39]Saba Q. Yahyaa, Madalina M. Drugan, Bernard Manderick:
Annealing linear scalarized based multi-objective multi-armed bandit algorithm. CEC 2015: 1738-1745 - [c38]Madalina M. Drugan:
Stochastic Pareto local search for many objective quadratic assignment problem instances. CEC 2015: 1754-1761 - [c37]Madalina M. Drugan:
Linear Scalarization for Pareto Front Identification in Stochastic Environments. EMO (2) 2015: 156-171 - [c36]Madalina M. Drugan:
Multi-objective optimization perspectives on reinforcement learning algorithms using reward vectors. ESANN 2015 - [c35]Nixon K. Ronoh, Reuben Odoyo, Edna Milgo, Madalina M. Drugan, Bernard Manderick:
Bernoulli bandits: an empirical comparison. ESANN 2015 - [c34]Madalina M. Drugan:
Efficient Real-Parameter Single Objective Optimizer Using Hierarchical CMA-ES Solvers. EVOLVE 2015: 131-145 - [c33]Madalina M. Drugan:
Synergies between Evolutionary Algorithms and Reinforcement Learning. GECCO (Companion) 2015: 723-740 - [c32]Saba Q. Yahyaa, Madalina M. Drugan, Bernard Manderick:
Thompson Sampling in the Adaptive Linear Scalarized Multi Objective Multi Armed Bandit. ICAART (2) 2015: 55-65 - [c31]Madalina M. Drugan, Bernard Manderick:
Exploration Versus Exploitation Trade-off in Infinite Horizon Pareto Multi-armed Bandits Algorithms. ICAART (2) 2015: 66-77 - [c30]Madalina M. Drugan:
Infinite Horizon Multi-armed Bandits with Reward Vectors: Exploration/Exploitation Trade-off. ICAART (Revised Selected Papers) 2015: 128-144 - [c29]Madalina M. Drugan:
Scalarized Lower Upper Confidence Bound Algorithm. LION 2015: 229-235 - [c28]Aldeida Aleti, Madalina M. Drugan:
Adaptive Neighbourhood Search for the Component Deployment Problem. SSBSE 2015: 188-202 - [c27]Michiel Van De Steeg, Madalina M. Drugan, Marco A. Wiering:
Temporal Difference Learning for the Game Tic-Tac-Toe 3D: Applying Structure to Neural Networks. SSCI 2015: 564-570 - [c26]Saba Q. Yahyaa, Madalina M. Drugan:
Correlated Gaussian Multi-Objective Multi-Armed Bandit Across Arms Algorithm. SSCI 2015: 593-600 - [c25]Madalina M. Drugan:
Approximative Pareto Front Identification. SSCI 2015: 869-876 - 2014
- [c24]Madalina M. Drugan, Ann Nowé, Bernard Manderick:
Pareto Upper Confidence Bounds algorithms: An empirical study. ADPRL 2014: 1-8 - [c23]Marco A. Wiering, Maikel Withagen, Madalina M. Drugan:
Model-based multi-objective reinforcement learning. ADPRL 2014: 1-6 - [c22]Saba Q. Yahyaa, Madalina M. Drugan, Bernard Manderick:
Annealing-pareto multi-objective multi-armed bandit algorithm. ADPRL 2014: 1-8 - [c21]Saba Q. Yahyaa, Madalina M. Drugan, Bernard Manderick:
Linear Scalarized Knowledge Gradient in the Multi-Objective Multi-Armed Bandits Problem. ESANN 2014 - [c20]Saba Q. Yahyaa, Madalina M. Drugan, Bernard Manderick:
Knowledge Gradient for Multi-objective Multi-armed Bandit Algorithms. ICAART (1) 2014: 74-83 - [c19]Saba Q. Yahyaa, Madalina M. Drugan, Bernard Manderick:
The scalarized multi-objective multi-armed bandit problem: An empirical study of its exploration vs. exploitation tradeoff. IJCNN 2014: 2290-2297 - [c18]Madalina M. Drugan, Ann Nowé:
Scalarization based Pareto optimal set of arms identification algorithms. IJCNN 2014: 2690-2697 - [c17]Madalina M. Drugan:
Multi-objective Quadratic Assignment Problem Instances Generator with a Known Optimum Solution. PPSN 2014: 559-568 - [c16]Madalina M. Drugan, Pedro Isasi, Bernard Manderick:
Schemata Bandits for Binary Encoded Combinatorial Optimisation Problems. SEAL 2014: 299-310 - 2013
- [c15]Kristof Van Moffaert, Madalina M. Drugan, Ann Nowé:
Scalarized multi-objective reinforcement learning: Novel design techniques. ADPRL 2013: 191-199 - [c14]Tim Brys, Madalina M. Drugan, Ann Nowé:
Meta-Evolutionary Algorithms and recombination operators for satisfiability solving in fuzzy logics. IEEE Congress on Evolutionary Computation 2013: 1060-1067 - [c13]Francesco Puglierin, Madalina M. Drugan, Marco A. Wiering:
Bandit-Inspired Memetic Algorithms for solving Quadratic Assignment Problems. IEEE Congress on Evolutionary Computation 2013: 2078-2085 - [c12]Madalina M. Drugan:
Instance generator for the quadratic assignment problem with additively decomposable cost function. IEEE Congress on Evolutionary Computation 2013: 2086-2093 - [c11]Madalina M. Drugan:
Sets of interacting scalarization functions in local search for multi-objective combinatorial optimization problems. MCDM 2013: 41-47 - [c10]Kristof Van Moffaert, Madalina M. Drugan, Ann Nowé:
Hypervolume-Based Multi-Objective Reinforcement Learning. EMO 2013: 352-366 - [c9]Madalina M. Drugan:
Cartesian product of scalarization functions for many-objective QAP instances with correlated flow matrices: cartesian product of scalarization functions. GECCO 2013: 527-534 - [c8]Tim Brys, Madalina M. Drugan, Peter A. N. Bosman, Martine De Cock, Ann Nowé:
Solving satisfiability in fuzzy logics by mixing CMA-ES. GECCO 2013: 1125-1132 - [c7]Tim Brys, Madalina M. Drugan, Peter A. N. Bosman, Martine De Cock, Ann Nowé:
Local search and restart strategies for satisfiability solving in fuzzy logics. GEFS 2013: 52-59 - [c6]Madalina M. Drugan, Ann Nowé:
Designing multi-objective multi-armed bandits algorithms: A study. IJCNN 2013: 1-8 - 2012
- [j5]Madalina M. Drugan, Dirk Thierens:
Stochastic Pareto local search: Pareto neighbourhood exploration and perturbation strategies. J. Heuristics 18(5): 727-766 (2012) - 2011
- [c5]Madalina M. Drugan, Dirk Thierens:
Generalized adaptive pursuit algorithm for genetic pareto local search algorithms. GECCO 2011: 1963-1970 - 2010
- [j4]Madalina M. Drugan, Dirk Thierens:
Geometrical Recombination Operators for Real-Coded Evolutionary MCMCs. Evol. Comput. 18(2): 157-198 (2010) - [j3]Madalina M. Drugan, Dirk Thierens:
Recombination operators and selection strategies for evolutionary Markov Chain Monte Carlo algorithms. Evol. Intell. 3(2): 79-101 (2010) - [j2]Madalina M. Drugan, Marco A. Wiering:
Feature selection for Bayesian network classifiers using the MDL-FS score. Int. J. Approx. Reason. 51(6): 695-717 (2010) - [c4]Madalina M. Drugan, Dirk Thierens:
Path-Guided Mutation for Stochastic Pareto Local Search Algorithms. PPSN (1) 2010: 485-495
2000 – 2009
- 2009
- [j1]Bas van Breukelen, Henk W. P. van den Toorn, Madalina M. Drugan, Albert J. R. Heck:
StatQuant: a post-quantification analysis toolbox for improving quantitative mass spectrometry. Bioinform. 25(11): 1472-1473 (2009) - 2006
- [b1]Madalina M. Drugan:
Conditional log-likelihood MDL and Evolutionary MCMC. Utrecht University, Netherlands, 2006 - 2005
- [c3]Madalina M. Drugan, Dirk Thierens:
Recombinative EMCMC algorithms. Congress on Evolutionary Computation 2005: 2024-2031 - 2004
- [c2]Madalina M. Drugan, Linda C. van der Gaag:
A New MDL-Based Function for Feature Selection for Bayesian Network Classifiers. ECAI 2004: 999-1000 - 2003
- [c1]Madalina M. Drugan, Dirk Thierens:
Evolutionary Markov Chain Monte Carlo. Artificial Evolution 2003: 63-76
Coauthor Index
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