Robert Kennes
Impact in
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- Multi-Criteria Decision Making
- Artificial Intelligence top 1%
- Bayesian Modeling and Causal Inference
- Logic, Reasoning, and Knowledge
- Target Tracking and Data Fusion in Sensor Networks
- AI-based Problem Solving and Planning
Papers in
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- Logic, Reasoning, and Knowledge 5
- Bayesian Modeling and Causal Inference 4
- AI-based Problem Solving and Planning 2
- Machine Learning and Algorithms 1
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- Epistemology, Ethics, and Metaphysics 1
- Co-authors
- Philippe Smets (3 shared papers)Alessandro Saffiotti (1 shared paper)Yen‐Teh Hsia (1 shared paper)Hong Bin Xu (1 shared paper)Hong Mei Xu (1 shared paper)
- Journals
- Artificial Intelligence (1 paper)Lecture notes in computer science (2 papers)Studies in fuzziness and soft computing (1 paper)IEEE Transactions on Systems Man and Cybernetics (1 paper)John Wiley & Sons, Inc. eBooks (1 paper)
- Partner nations
- Belgium
In The Last Decade
Robert Kennes
7 papers receiving 1.9k citations
Robert Kennes's Hit Papers
Peers
Comparison fields: 5 of 108
- Management Science and Operations Research 773
- Artificial Intelligence 1.3k
- Computational Theory and Mathematics 377
- Statistics, Probability and Uncertainty 145
- Statistics and Probability 165
Countries citing papers authored by Robert Kennes
This map shows the geographic impact of Robert Kennes'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 Robert Kennes with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Robert Kennes more than expected).
Fields of papers citing papers by Robert Kennes
This network shows the impact of papers produced by Robert Kennes. 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 Robert Kennes. The network helps show where Robert Kennes may publish in the future.
Co-authors
The 5 scholars most cited alongside Robert Kennes, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | The transferable belief model Hit paper breakdown → | 1994 | 1739 |
| 2 | 1991 | 130 | |
| 3 | 1992 | 79 | |
| 4 | 2008 | 39 | |
| 5 | 2005 | 15 | |
| 6 | 1991 | 13 | |
| 7 | Steps toward efficient implementation on Dempster-Shafer theory | 1994 | 10 |
About Robert Kennes
Robert Kennes is a scholar working on Artificial Intelligence, Philosophy, Management Science and Operations Research, Computational Theory and Mathematics and Food Science, having authored 7 papers that have together received 2.0k indexed citations. Recurring topics across this work include Logic, Reasoning, and Knowledge (5 papers), Bayesian Modeling and Causal Inference (4 papers), AI-based Problem Solving and Planning (2 papers), Epistemology, Ethics, and Metaphysics (1 paper), Advanced Scientific Research Methods (1 paper), Formal Methods in Verification (1 paper), Machine Learning and Algorithms (1 paper) and Multi-Criteria Decision Making (1 paper). The work is most often cited by research in Management Science and Operations Research (773 citations), Artificial Intelligence (1.3k citations), Computational Theory and Mathematics (377 citations), Statistics, Probability and Uncertainty (145 citations) and Statistics and Probability (165 citations). Robert Kennes has collaborated with scholars based in Belgium. Frequent co-authors include Philippe Smets, Alessandro Saffiotti, Yen‐Teh Hsia, Hong Bin Xu and Hong Mei Xu. Their work appears in journals such as Artificial Intelligence, Lecture notes in computer science, Studies in fuzziness and soft computing, IEEE Transactions on Systems Man and Cybernetics and John Wiley & Sons, Inc. eBooks.
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.