David André
Impact in
- Artificial Intelligence top 2%
- Evolutionary Algorithms and Applications
- Metaheuristic Optimization Algorithms Research
- Reinforcement Learning in Robotics
- AI-based Problem Solving and Planning
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- Advanced Multi-Objective Optimization Algorithms
Papers in
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- Evolutionary Algorithms and Applications 24
- Metaheuristic Optimization Algorithms Research 18
- Reinforcement Learning in Robotics 10
- Machine Learning and Algorithms 3
- Data Stream Mining Techniques 2
- Neural Networks and Applications 2
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- Viral Infectious Diseases and Gene Expression in Insects 5
- Gene Regulatory Network Analysis 4
- Co-authors
- John R. Koza (17 shared papers)Martin A. Keane (10 shared papers)Forrest H Bennett (4 shared papers)Stuart Russell (4 shared papers)Nir Friedman (2 shared papers)Richard Dearden (1 shared paper)Ronald Parr (1 shared paper)J. M. Forbes (1 shared paper)
- Journals
- Information Sciences (1 paper)Archives des maladies professionnelles et de médecine du travail/Archives des maladies professionnelles et de l'environnement (1 paper)Revue internationale de psychosociologie et de gestion des comportements organisationnels (1 paper)Uncertainty in Artificial Intelligence (2 papers)arXiv (Cornell University) (1 paper)
- Partner nations
- United StatesFranceCanada
In The Last Decade
David André
27 papers receiving 877 citations
Peers
Comparison fields: 5 of 100
- Artificial Intelligence 798
- Computational Theory and Mathematics 187
- Software 18
- Management Science and Operations Research 54
- Computer Science Applications 19
Countries citing papers authored by David André
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
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-authors
The 12 scholars most cited alongside David André, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 30 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Genetic Programming III: Darwinian Invention and Problem Solving | 1999 | 457 |
| 2 | 2002 | 134 | |
| 3 | Programmable Reinforcement Learning Agents | 2000 | 64 |
| 4 | Parallel genetic programming: a scalable implementation using the transputer network architecture | 1996 | 59 |
| 5 | 2013 | 47 | |
| 6 | Parallel Genetic Programming on a Network of Transputers | 1995 | 47 |
| 7 | 1998 | 40 | |
| 8 | Generalized Prioritized Sweeping | 1997 | 32 |
| 9 | A Paralle Implementation of Genetic Programming that Achieves Super-Linear Performance. | 1996 | 17 |
| 10 | 1998 | 16 | |
| 11 | 1997 | 13 | |
| 12 | Evolution of Iteration in Genetic Programming. | 1996 | 12 |
| 13 | Toward Evolution of Electronic Animals Using Genetic Programming | 2004 | 9 |
| 14 | Evolution of Intricate Long-Distance Communication Signals in Cellular Automata Using Genetic Programming | 2004 | 8 |
| 15 | The automatic programming of agents that learn mental models and create simple plans of action | 1995 | 7 |
| 16 | The Evolution of Agents that Build Mental Models and Create Simple Plans Using Genetic Programming | 1995 | 6 |
| 17 | Practical reinforcement learning in continuous domains | 2000 | 6 |
| 18 | The Design of Analog Circuits by Means of Genetic Programming | 2004 | 4 |
| 19 | Evolution of Both the Architecture and the Sequence of Work-Performing Steps of a Computer Program Using Genetic Programming with Architecture-Altering Operations | 1995 | 4 |
| 20 | 2000 | 4 |
About David André
David André is a scholar working on Artificial Intelligence, Molecular Biology, Computational Theory and Mathematics, Plant Science and General Health Professions, having authored 30 papers that have together received 1.0k indexed citations. Recurring topics across this work include Evolutionary Algorithms and Applications (24 papers), Metaheuristic Optimization Algorithms Research (18 papers), Reinforcement Learning in Robotics (10 papers), Viral Infectious Diseases and Gene Expression in Insects (5 papers), Gene Regulatory Network Analysis (4 papers), Machine Learning and Algorithms (3 papers), Data Stream Mining Techniques (2 papers) and Neural Networks and Applications (2 papers). The work is most often cited by research in Artificial Intelligence (798 citations), Computational Theory and Mathematics (187 citations), Software (18 citations), Management Science and Operations Research (54 citations) and Computer Science Applications (19 citations). David André has collaborated with scholars based in United States, France and Canada. Frequent co-authors include John R. Koza, Martin A. Keane, Forrest H Bennett, Stuart Russell, Nir Friedman, Richard Dearden, Ronald Parr, J. M. Forbes, Alessandro Pasquale De Rosa and Bhaskara Marthi. Their work appears in journals such as Information Sciences, Archives des maladies professionnelles et de médecine du travail/Archives des maladies professionnelles et de l'environnement, Revue internationale de psychosociologie et de gestion des comportements organisationnels, Uncertainty in Artificial Intelligence and arXiv (Cornell University).
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.