A. E. Eiben

18.3k total citations · 7 hit papers
167 papers, 9.2k citations indexed

About

A. E. Eiben is a scholar working on Artificial Intelligence, Mechanical Engineering and Computational Theory and Mathematics. According to data from OpenAlex, A. E. Eiben has authored 167 papers receiving a total of 9.2k indexed citations (citations by other indexed papers that have themselves been cited), including 130 papers in Artificial Intelligence, 60 papers in Mechanical Engineering and 22 papers in Computational Theory and Mathematics. Recurrent topics in A. E. Eiben's work include Evolutionary Algorithms and Applications (103 papers), Reinforcement Learning in Robotics (79 papers) and Modular Robots and Swarm Intelligence (59 papers). A. E. Eiben is often cited by papers focused on Evolutionary Algorithms and Applications (103 papers), Reinforcement Learning in Robotics (79 papers) and Modular Robots and Swarm Intelligence (59 papers). A. E. Eiben collaborates with scholars based in Netherlands, United Kingdom and Germany. A. E. Eiben's co-authors include James E. Smith, Zbigniew Michalewicz, Robert Hinterding, S. K. Smit, Volker Nannen, Giorgos Karafotias, Mark Hoogendoorn, Evert Haasdijk, Nicolas Bredèche and Tamás Nepusz and has published in prestigious journals such as Nature, Nature Communications and PLoS ONE.

In The Last Decade

A. E. Eiben

156 papers receiving 8.7k citations

Hit Papers

Introduction to Evolution... 1999 2026 2008 2017 2003 1999 2015 2011 2018 500 1000 1.5k 2.0k 2.5k

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
A. E. Eiben 5.1k 2.4k 1.1k 933 929 167 9.2k
Thomas Bäck 6.4k 1.2× 3.9k 1.6× 868 0.8× 1.1k 1.2× 687 0.7× 315 12.3k
William G. Macready 6.2k 1.2× 3.0k 1.2× 777 0.7× 811 0.9× 356 0.4× 35 10.6k
David B. Fogel 5.5k 1.1× 1.9k 0.8× 624 0.6× 688 0.7× 443 0.5× 170 10.0k
Gary B. Lamont 4.8k 0.9× 5.0k 2.1× 947 0.9× 1.3k 1.3× 994 1.1× 129 10.9k
Hans–Paul Schwefel 4.8k 0.9× 2.8k 1.2× 523 0.5× 723 0.8× 527 0.6× 48 8.5k
Maurice Clerc 5.0k 1.0× 2.3k 1.0× 883 0.8× 708 0.8× 566 0.6× 39 9.9k
D. E. Goldberg 3.8k 0.7× 1.6k 0.7× 917 0.8× 1.1k 1.2× 731 0.8× 6 10.2k
David Corne 4.0k 0.8× 3.6k 1.5× 492 0.5× 1.3k 1.4× 521 0.6× 161 7.8k
Daniel Molina 8.7k 1.7× 3.5k 1.5× 688 0.6× 1.1k 1.1× 331 0.4× 64 13.5k
John R. Koza 7.4k 1.4× 1.5k 0.6× 474 0.4× 486 0.5× 722 0.8× 74 11.8k

Countries citing papers authored by A. E. Eiben

Since Specialization
Citations

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

Fields of papers citing papers by A. E. Eiben

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by A. E. Eiben. 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 A. E. Eiben. The network helps show where A. E. Eiben may publish in the future.

Co-authorship network of co-authors of A. E. Eiben

This figure shows the co-authorship network connecting the top 25 collaborators of A. E. Eiben. A scholar is included among the top collaborators of A. E. Eiben 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 A. E. Eiben. A. E. Eiben 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.
Eiben, A. E., et al.. (2025). Lamarckian Inheritance Improves Robot Evolution in Dynamic Environments. IEEE Transactions on Evolutionary Computation. 1–1.
2.
Hart, Emma, et al.. (2024). Towards a Unified Framework for Software-Hardware Integration in Evolutionary Robotics. Robotics. 13(11). 157–157. 1 indexed citations
3.
Hindriks, Koen V., et al.. (2024). ``Give Me an Example Like This'': Episodic Active Reinforcement Learning from Demonstrations. VU Research Portal. 287–295.
4.
Ferrante, Eliseo, et al.. (2024). A model-free method to learn multiple skills in parallel on modular robots. Nature Communications. 15(1). 6267–6267. 1 indexed citations
5.
Luo, Jie, et al.. (2023). Enhancing robot evolution through Lamarckian principles. Scientific Reports. 13(1). 21109–21109. 1 indexed citations
6.
Hart, Emma, Zhongxue Gan, Alan Winfield, et al.. (2023). Evaluation of Frameworks That Combine Evolution and Learning to Design Robots in Complex Morphological Spaces. IEEE Transactions on Evolutionary Computation. 28(6). 1561–1574. 11 indexed citations
7.
Ferrante, Eliseo, et al.. (2022). Environment induced emergence of collective behavior in evolving swarms with limited sensing. Proceedings of the Genetic and Evolutionary Computation Conference. 31–39. 5 indexed citations
8.
Turgut, Ali Emre, et al.. (2022). Collective gradient perception with a flying robot swarm. Swarm Intelligence. 17(1-2). 117–146. 6 indexed citations
9.
Węglarz‐Tomczak, Ewelina, Jakub M. Tomczak, A. E. Eiben, & Stanley Brul. (2021). Population-Based Parameter Identification for Dynamical Models of Biological Networks with an Application to Saccharomyces cerevisiae. Processes. 9(1). 98–98. 5 indexed citations
10.
Lan, Gongjin, Jakub M. Tomczak, Diederik M. Roijers, & A. E. Eiben. (2021). Time efficiency in optimization with a bayesian-Evolutionary algorithm. Swarm and Evolutionary Computation. 69. 100970–100970. 44 indexed citations
11.
Vásárhelyi, Gábor, Csaba Virágh, Gergő Somorjai, et al.. (2018). Optimized flocking of autonomous drones in confined environments. Science Robotics. 3(20). 368 indexed citations breakdown →
12.
Glette, Kyrre, et al.. (2017). Analysis of Lamarckian evolution in morphologically evolving robots. 1 indexed citations
13.
Nannen, Volker & A. E. Eiben. (2007). Relevance estimation and value calibration of evolutionary algorithm parameters. Data Archiving and Networked Services (DANS). 975–980. 93 indexed citations
14.
Eiben, A. E., et al.. (2007). Parameter calibration using meta-algorithms. 71–78. 29 indexed citations
15.
Eiben, A. E., et al.. (2002). Solving 3-SAT by GAs adapting constraint weights. 81–86. 20 indexed citations
16.
Craenen, Bart & A. E. Eiben. (2001). Stepwise adaption of weights with refinement and decay on constraint satisfaction problems. Genetic and Evolutionary Computation Conference. 291–298. 10 indexed citations
17.
Eiben, A. E., Bart Jansen, Zbigniew Michalewicz, & Ben Paechter. (2000). Solving CSPs using self-adaptive constraint weights: how to prevent EAs from cheating. Research Output (Edinburgh Napier University). 128–134. 5 indexed citations
18.
Eiben, A. E., et al.. (1999). Population dynamics and emerging mental features in AEGIS. Genetic and Evolutionary Computation Conference. 1257–1264. 2 indexed citations
19.
Eiben, A. E.. (1998). Parallel problem solving from nature-PPSN V : 5th International Conference, Amsterdam, The Netherlands, September 27-30, 1998 : proceedings. Springer eBooks. 9 indexed citations
20.
Eiben, A. E., et al.. (1998). On Evolutionary Exploration and Exploitation. Fundamenta Informaticae. 35(1-4). 35–50. 225 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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