David André

2.5k total citations
30 papers, 1.0k citations indexed

About

David André is a scholar working on Artificial Intelligence, Molecular Biology and Computational Theory and Mathematics. According to data from OpenAlex, David André has authored 30 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Artificial Intelligence, 10 papers in Molecular Biology and 2 papers in Computational Theory and Mathematics. Recurrent topics in David André's work include Evolutionary Algorithms and Applications (24 papers), Metaheuristic Optimization Algorithms Research (18 papers) and Reinforcement Learning in Robotics (10 papers). David André is often cited by papers focused on Evolutionary Algorithms and Applications (24 papers), Metaheuristic Optimization Algorithms Research (18 papers) and Reinforcement Learning in Robotics (10 papers). David André collaborates with scholars based in United States, France and Portugal. David André's co-authors include John R. Koza, Martin A. Keane, Forrest H Bennett, Stuart Russell, Nir Friedman, Richard Dearden, Ronald Parr, J. M. Forbes, Bhaskara Marthi and Paulo Aguiar and has published in prestigious journals such as Information Sciences, international conference on Genetic algorithms and Archives des maladies professionnelles et de médecine du travail/Archives des maladies professionnelles et de l'environnement.

In The Last Decade

David André

27 papers receiving 877 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
David André United States 12 798 187 177 94 65 30 1.0k
Edgar Galván Ireland 16 610 0.8× 119 0.6× 135 0.8× 116 1.2× 47 0.7× 62 856
Meng Hiot Lim Singapore 14 666 0.8× 333 1.8× 49 0.3× 151 1.6× 57 0.9× 28 1.1k
Guillermo Leguizamón Argentina 12 418 0.5× 189 1.0× 124 0.7× 36 0.4× 40 0.6× 56 667
Xianshun Chen Singapore 7 545 0.7× 276 1.5× 49 0.3× 58 0.6× 47 0.7× 14 874
Tobias Blickle Switzerland 6 351 0.4× 166 0.9× 52 0.3× 128 1.4× 37 0.6× 7 791
Rong Miao China 13 371 0.5× 323 1.7× 120 0.7× 36 0.4× 54 0.8× 33 860
Peter Merz Germany 13 506 0.6× 262 1.4× 52 0.3× 103 1.1× 44 0.7× 32 882
Albert Orriols-Puig Spain 15 688 0.9× 75 0.4× 101 0.6× 73 0.8× 20 0.3× 33 874
Prabhas Chongstitvatana Thailand 12 358 0.4× 123 0.7× 64 0.4× 59 0.6× 44 0.7× 103 707
Bryant A. Julstrom United States 16 440 0.6× 336 1.8× 38 0.2× 199 2.1× 61 0.9× 48 906

Countries citing papers authored by David André

Since Specialization
Citations

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

Fields of papers citing papers by David André

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of David André

This figure shows the co-authorship network connecting the top 25 collaborators of David André. A scholar is included among the top collaborators of David André 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 David André. David André 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.
André, David, et al.. (2020). Les émotions en actions : la mise en vigilance des policiers de primo intervention. Revue internationale de psychosociologie et de gestion des comportements organisationnels. Vol. XXVI(65). 107–126. 1 indexed citations
2.
André, David, et al.. (2018). Comment maintenir au même poste un psychotique durant 30 ans ?. Archives des maladies professionnelles et de médecine du travail/Archives des maladies professionnelles et de l'environnement. 79(3). 290–290.
3.
Marthi, Bhaskara, Stuart Russell, & David André. (2006). A compact, hierarchically optimal Q-function decomposition. Uncertainty in Artificial Intelligence. 332–340. 3 indexed citations
4.
Marthi, Bhaskara, Stuart Russell, & David André. (2006). A compact, hierarchical Q-function decomposition. Uncertainty in Artificial Intelligence. 1 indexed citations
5.
Koza, John R., et al.. (2004). Use of Architecture-Altering Operations to Dynamically Adapt a Three-Way Analog Source Identification Circuit to Accommodate a New Source. 1 indexed citations
6.
André, David, Forrest H Bennett, & John R. Koza. (2004). Evolution of Intricate Long-Distance Communication Signals in Cellular Automata Using Genetic Programming. 8 indexed citations
7.
Koza, John R., David André, & Martin A. Keane. (2004). The Design of Analog Circuits by Means of Genetic Programming. 4 indexed citations
8.
Koza, John R., et al.. (2004). Evolution of a Tri-State Frequency Discriminator for the Source Identification Problem using Genetic Programming.
9.
Koza, John R., David André, & Martin A. Keane. (2004). Evolution of a Low-Distortion, Low-Bias 60 Decibel Op Amp with Good Frequency Generalization using Genetic Programming. 3 indexed citations
10.
André, David & Stuart Russell. (2002). State abstraction for programmable reinforcement learning agents. National Conference on Artificial Intelligence. 119–125. 134 indexed citations
11.
André, David & Stuart Russell. (2000). Programmable Reinforcement Learning Agents. Neural Information Processing Systems. 13. 1019–1025. 64 indexed citations
12.
Forbes, J. M. & David André. (2000). Practical reinforcement learning in continuous domains. UC Berkeley. 6 indexed citations
13.
André, David & John R. Koza. (1998). A parallel implementation of genetic programming that achieves super-linear performance. Information Sciences. 106(3-4). 201–218. 40 indexed citations
14.
André, David, Nir Friedman, & Ronald Parr. (1997). Generalized Prioritized Sweeping. Neural Information Processing Systems. 10. 1001–1007. 32 indexed citations
15.
Koza, John R., Forrest H Bennett, David André, & Martin A. Keane. (1997). Evolution using genetic programming of a low-distortion, 96 decibel operational amplifier. 207–216. 13 indexed citations
16.
André, David & John R. Koza. (1996). Parallel genetic programming: a scalable implementation using the transputer network architecture. MIT Press eBooks. 317–337. 59 indexed citations
17.
André, David & John R. Koza. (1996). A Paralle Implementation of Genetic Programming that Achieves Super-Linear Performance.. Parallel and Distributed Processing Techniques and Applications. 1163–1174. 17 indexed citations
18.
Koza, John R. & David André. (1996). Evolution of Iteration in Genetic Programming.. 24(3). 469–478. 12 indexed citations
19.
André, David. (1995). The automatic programming of agents that learn mental models and create simple plans of action. International Joint Conference on Artificial Intelligence. 741–747. 7 indexed citations
20.
André, David. (1995). The Evolution of Agents that Build Mental Models and Create Simple Plans Using Genetic Programming. international conference on Genetic algorithms. 248–255. 6 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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