Katja Verbeeck

1.4k total citations
60 papers, 670 citations indexed

About

Katja Verbeeck is a scholar working on Management Science and Operations Research, Artificial Intelligence and Industrial and Manufacturing Engineering. According to data from OpenAlex, Katja Verbeeck has authored 60 papers receiving a total of 670 indexed citations (citations by other indexed papers that have themselves been cited), including 35 papers in Management Science and Operations Research, 22 papers in Artificial Intelligence and 17 papers in Industrial and Manufacturing Engineering. Recurrent topics in Katja Verbeeck's work include Scheduling and Timetabling Solutions (13 papers), Game Theory and Applications (12 papers) and Reinforcement Learning in Robotics (12 papers). Katja Verbeeck is often cited by papers focused on Scheduling and Timetabling Solutions (13 papers), Game Theory and Applications (12 papers) and Reinforcement Learning in Robotics (12 papers). Katja Verbeeck collaborates with scholars based in Belgium, Netherlands and Denmark. Katja Verbeeck's co-authors include Ann Nowé, Karl Tuyls, Patrick De Causmaecker, Greet Van den Berghe, Tom Lenaerts, Tony Wauters, Greet Vanden Berghe, Mustafa Mısır, Peter Vrancx and Steven de Jong and has published in prestigious journals such as Journal of the Operational Research Society, Applied Soft Computing and IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics).

In The Last Decade

Katja Verbeeck

58 papers receiving 626 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Katja Verbeeck Belgium 16 327 253 212 144 79 60 670
Yann Chevaleyre France 16 383 1.2× 316 1.2× 63 0.3× 285 2.0× 24 0.3× 44 909
Janet Bruten United States 7 101 0.3× 203 0.8× 87 0.4× 426 3.0× 22 0.3× 10 787
K. Suzanne Barber United States 10 61 0.2× 220 0.9× 122 0.6× 84 0.6× 37 0.5× 70 443
Noam Hazon Israel 14 195 0.6× 121 0.5× 30 0.1× 268 1.9× 32 0.4× 40 705
Rob Powers United States 10 269 0.8× 403 1.6× 10 0.0× 159 1.1× 81 1.0× 11 789
Peng Cheng China 16 219 0.7× 247 1.0× 36 0.2× 174 1.2× 38 0.5× 66 999
Yuhong Yan Canada 16 47 0.1× 292 1.2× 47 0.2× 393 2.7× 21 0.3× 59 773
Bikramjit Banerjee United States 11 101 0.3× 370 1.5× 11 0.1× 96 0.7× 38 0.5× 44 500
Fenghui Ren Australia 14 112 0.3× 201 0.8× 14 0.1× 85 0.6× 92 1.2× 60 596
Bushra Alhijawi Jordan 11 51 0.2× 267 1.1× 27 0.1× 139 1.0× 69 0.9× 35 681

Countries citing papers authored by Katja Verbeeck

Since Specialization
Citations

This map shows the geographic impact of Katja Verbeeck'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 Katja Verbeeck with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Katja Verbeeck more than expected).

Fields of papers citing papers by Katja Verbeeck

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Katja Verbeeck. 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 Katja Verbeeck. The network helps show where Katja Verbeeck may publish in the future.

Co-authorship network of co-authors of Katja Verbeeck

This figure shows the co-authorship network connecting the top 25 collaborators of Katja Verbeeck. A scholar is included among the top collaborators of Katja Verbeeck 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 Katja Verbeeck. Katja Verbeeck 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.
Wauters, Tony, Katja Verbeeck, Greet Van den Berghe, & Patrick De Causmaecker. (2010). A Game Theoretic Approach to Decentralized Multi-Project Scheduling (Extended Abstract). Lirias (KU Leuven). 1415–1416. 5 indexed citations
2.
Vrancx, Peter, Katja Verbeeck, & Ann Nowé. (2010). Learning to take turns.. 1–7. 1 indexed citations
3.
Wauters, Tony, Katja Verbeeck, Greet Vanden Berghe, & Patrick De Causmaecker. (2010). A game theoretic approach to decentralized multi-project scheduling. Adaptive Agents and Multi-Agents Systems. 1415–1416. 5 indexed citations
4.
Vrancx, Peter, Katja Verbeeck, & Ann Nowé. (2010). Analyzing the dynamics of stigmergetic interactions through pheromone games. Theoretical Computer Science. 411(21). 2116–2126. 2 indexed citations
5.
Wauters, Tony, Katja Verbeeck, Greet Van den Berghe, & Patrick De Causmaecker. (2009). A multi-agent learning approach for the multi-mode resource-constrained project scheduling problem. Lirias (KU Leuven). 1–8. 11 indexed citations
6.
Michiels, Sam, et al.. (2009). A sensor middleware and agent-based communication platform for supply-chain management. Lirias (KU Leuven). 1409–1410. 1 indexed citations
7.
Jong, Steven de, Karl Tuyls, & Katja Verbeeck. (2008). Artificial agents learning human fairness. Adaptive Agents and Multi-Agents Systems. 863–870. 14 indexed citations
8.
Vrancx, Peter, Katja Verbeeck, & Ann Nowé. (2008). Decentralized Learning in Markov Games. IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics). 38(4). 976–981. 52 indexed citations
9.
Souffriau, Wouter, et al.. (2008). Dynamic scheduling of multi-media streams in home automation systems. Adaptive Agents and Multi-Agents Systems. 1683–1684. 1 indexed citations
10.
Jong, Steven de, Karl Tuyls, Katja Verbeeck, & Nico Roos. (2007). Priority Awareness: Towards a Computational Model of Human Fairness for Multi-agent Systems.. Adaptive Agents and Multi-Agents Systems. 117–128. 3 indexed citations
11.
Tuyls, Karl, et al.. (2006). Learning and Adaptation in Multi-Agent Systems. Lecture notes in computer science. 3898. 3 indexed citations
12.
Verbeeck, Katja, et al.. (2006). Learning and adaption in multi-agent systems : first international workshop, LAMAS 2005, Utrecht, the Netherlands, July 25, 2005, revised selected papers. Springer eBooks. 2 indexed citations
13.
Nowé, Ann, Katja Verbeeck, & Maarten Peeters. (2006). Learning Automata as a Basis for Multi Agent Reinforcement Learning.. Lecture notes in computer science. 3898. 71–85. 12 indexed citations
14.
Kaminka, Gal A., et al.. (2005). Proceedings of the Third European Workshop on Multi-Agent Systems. (EUMAS 2005). 1 indexed citations
15.
Hesselink, Wim H., Gerben G. Meyer, Katja Verbeeck, et al.. (2005). Proceedings of the 17th Belgium-Netherlands Conference on Artificial Intelligence. 17 indexed citations
16.
Peeters, Maarten, Katja Verbeeck, & Ann Nowé. (2004). Multi-Agent Learning in Conflicting Multi-Level Games with Incomplete Information.. VUBIR (Vrije Universiteit Brussel). 73–80. 1 indexed citations
17.
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
18.
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
19.
Lenaerts, Tom, Bernard Manderick, Ann Nowé, et al.. (2001). Niching and Evolutionary Transitions in MAS. 1 indexed citations
20.
Nowé, Ann & Katja Verbeeck. (1999). Distributed Reinforcement Learning, load-based routing a case study. VUBIR (Vrije Universiteit Brussel). 4 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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