Bernard Manderick

2.9k total citations
85 papers, 1.5k citations indexed

About

Bernard Manderick is a scholar working on Artificial Intelligence, Management Science and Operations Research and Molecular Biology. According to data from OpenAlex, Bernard Manderick has authored 85 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 47 papers in Artificial Intelligence, 23 papers in Management Science and Operations Research and 18 papers in Molecular Biology. Recurrent topics in Bernard Manderick's work include Reinforcement Learning in Robotics (12 papers), Evolutionary Algorithms and Applications (12 papers) and Advanced Bandit Algorithms Research (10 papers). Bernard Manderick is often cited by papers focused on Reinforcement Learning in Robotics (12 papers), Evolutionary Algorithms and Applications (12 papers) and Advanced Bandit Algorithms Research (10 papers). Bernard Manderick collaborates with scholars based in Belgium, Spain and Netherlands. Bernard Manderick's co-authors include Piet Spiessens, Thomas Hamelryck, Sam Maes, Bram Vanschoenwinkel, Karl Tuyls, Reinhard Männer, Alberto Colorni, Vittorio Maniezzo, Marco Dorigo and Ann Nowé and has published in prestigious journals such as Bioinformatics, Expert Systems with Applications and BMC Bioinformatics.

In The Last Decade

Bernard Manderick

77 papers receiving 1.4k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Bernard Manderick Belgium 14 900 284 278 162 147 85 1.5k
Viggo Kann Sweden 18 682 0.8× 690 2.4× 167 0.6× 188 1.2× 271 1.8× 53 2.1k
Jean-Michel Renders France 13 817 0.9× 214 0.8× 146 0.5× 58 0.4× 300 2.0× 54 1.7k
Rosni Abdullah Malaysia 22 656 0.7× 153 0.5× 181 0.7× 52 0.3× 167 1.1× 146 1.6k
Philipp Rohlfshagen United Kingdom 13 1.3k 1.5× 206 0.7× 62 0.2× 177 1.1× 386 2.6× 24 2.1k
Michèle Sébag France 24 1.0k 1.2× 461 1.6× 85 0.3× 62 0.4× 163 1.1× 86 1.7k
Nagarajan Natarajan United States 19 683 0.8× 182 0.6× 298 1.1× 30 0.2× 209 1.4× 63 1.6k
Randy Goebel Canada 21 742 0.8× 66 0.2× 196 0.7× 60 0.4× 190 1.3× 141 1.7k
Safaai Deris Malaysia 19 458 0.5× 131 0.5× 772 2.8× 147 0.9× 128 0.9× 179 1.5k
Guoliang Chen China 18 395 0.4× 303 1.1× 158 0.6× 63 0.4× 61 0.4× 98 1.3k
William F. Clocksin United Kingdom 18 1.0k 1.1× 343 1.2× 88 0.3× 98 0.6× 437 3.0× 53 1.9k

Countries citing papers authored by Bernard Manderick

Since Specialization
Citations

This map shows the geographic impact of Bernard Manderick's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Bernard Manderick with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bernard Manderick more than expected).

Fields of papers citing papers by Bernard Manderick

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Bernard Manderick. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Bernard Manderick. The network helps show where Bernard Manderick may publish in the future.

Co-authorship network of co-authors of Bernard Manderick

This figure shows the co-authorship network connecting the top 25 collaborators of Bernard Manderick. A scholar is included among the top collaborators of Bernard Manderick based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Bernard Manderick. Bernard Manderick is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Drugan, Mădălina M., et al.. (2015). Bernoulli bandits an empirical comparison. TU/e Research Portal. 59–64. 3 indexed citations
2.
Manderick, Bernard, et al.. (2012). STRING METHODS FOR FOLK TUNE GENRE CLASSIFICATION. International Symposium/Conference on Music Information Retrieval. 217–222. 18 indexed citations
3.
Manderick, Bernard, et al.. (2012). The Exploration vs Exploitation Trade-Off in Bandit Problems: An Empirical Study. The European Symposium on Artificial Neural Networks.
4.
Beule, Joachim De, et al.. (2011). Roth-Erev Learning in Signaling and Language Games. Dépôt institutionnel de l'Université libre de Bruxelles (Université Libre de Bruxelles). 23. 67–74. 4 indexed citations
5.
Meganck, Stijn, Sam Maes, Philippe Leray, & Bernard Manderick. (2006). Learning Semi-Markovian Causal Models using Experiments. VUBIR (Vrije Universiteit Brussel). 18(1). 195–206. 3 indexed citations
6.
Vanschoenwinkel, Bram & Bernard Manderick. (2005). Context-sensitive Kernel Functions : A Comparison Between Different Context Weights.. VUBIR (Vrije Universiteit Brussel). 134(6). 283–290. 3 indexed citations
7.
Meganck, Stijn, Sam Maes, & Bernard Manderick. (2005). Identification in Chain Multi-Agent Causal Models.. VUBIR (Vrije Universiteit Brussel). 1 indexed citations
8.
Maes, Sam, Stijn Meganck, & Bernard Manderick. (2005). Identification in Chain Multi-Agent Causal Models. The Florida AI Research Society. 791–792. 2 indexed citations
9.
Vanschoenwinkel, Bram & Bernard Manderick. (2005). Appropriate kernel functions for support vector machine learning with sequences of symbolic data. Lecture notes in computer science. 3635. 256–280. 3 indexed citations
10.
Maes, Sam, Stijn Meganck, & Bernard Manderick. (2004). Multi-Agent Identification of Causal Effects. VUBIR (Vrije Universiteit Brussel). 3 indexed citations
11.
Vanschoenwinkel, Bram & Bernard Manderick. (2003). A weighted polynomial information gain kernel for resolving prepositional phrase attachment ambiguities with support vector machines. International Joint Conference on Artificial Intelligence. 133–138. 3 indexed citations
12.
Vanschoenwinkel, Bram & Bernard Manderick. (2003). A Weighted Polynomial Information Gain Kernel for resolving PP attachment ambiguities with Support Vector Machines.. VUBIR (Vrije Universiteit Brussel). 4 indexed citations
13.
Tuyls, Karl, Tom Lenaerts, Katja Verbeeck, Sam Maes, & Bernard Manderick. (2002). Towards a relation between learning agents and evolutionary dynamics. Dépôt institutionnel de l'Université libre de Bruxelles (Université Libre de Bruxelles). 315–322. 7 indexed citations
14.
Tuyls, Karl, Sam Maes, & Bernard Manderick. (2002). Q-Learning in Simulated Robotic Soccer - Large State Spaces and Incomplete Information.. VUBIR (Vrije Universiteit Brussel). 226–232. 2 indexed citations
15.
Lenaerts, Tom, et al.. (2002). Testing the overall functional robustness of 2D CA phenotypes for development. Dépôt institutionnel de l'Université libre de Bruxelles (Université Libre de Bruxelles). 203–210. 1 indexed citations
16.
Lenaerts, Tom, Sam Maes, Karl Tuyls, et al.. (2001). Niching and evolutionary transitions in multi-agent systems. Dépôt institutionnel de l'Université libre de Bruxelles (Université Libre de Bruxelles). 309–312. 2 indexed citations
17.
Männer, Reinhard & Bernard Manderick. (1992). Parallel Problem Solving from Nature, 2: Proceedings of the Second Conference on Parallel Problem Solving from Nature, Brussels, Belgium, 28-30 September, 1992. Elsevier eBooks. 6 indexed citations
18.
Bersini, Hugues, et al.. (1992). In search of a good optimization-evolution crossover. Dépôt institutionnel de l'Université libre de Bruxelles (Université Libre de Bruxelles). 479–488. 7 indexed citations
19.
Spiessens, Piet & Bernard Manderick. (1991). A Massively Parallel Genetic Algorithm: Implementation and First Analysis.. VUBIR (Vrije Universiteit Brussel). 19(11). 279–287. 60 indexed citations
20.
Manderick, Bernard & Piet Spiessens. (1989). Fine-Grained Parallel Genetic Algorithms. international conference on Genetic algorithms. 428–433. 205 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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