David Tolpin
Impact in
Papers in
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- AI-based Problem Solving and Planning 4
- Bayesian Modeling and Causal Inference 4
- Artificial Intelligence in Games 3
- Reinforcement Learning in Robotics 2
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- Advanced Database Systems and Queries 2
- Constraint Satisfaction and Optimization 2
- Co-authors
- Solomon Eyal Shimony (7 shared papers)Ariel Felner (3 shared papers)Eli Boyarski (1 shared paper)Jan-Willem van de Meent (1 shared paper)Roni Stern (1 shared paper)Hongseok Yang (1 shared paper)Frank Wood (2 shared papers)Guni Sharon (1 shared paper)
- Journals
- IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics) (1 paper)Artificial Intelligence (1 paper)Intelligent Decision Technologies (1 paper)arXiv (Cornell University) (2 papers)Proceedings of the International Symposium on Combinatorial Search (2 papers)
- Partner nations
- IsraelUnited KingdomUnited States
In The Last Decade
David Tolpin
10 papers receiving 130 citations
Peers
Comparison fields: 5 of 41
- General Decision Sciences 10
- Software 11
- Computer Vision and Pattern Recognition 54
- Artificial Intelligence 83
- Management Science and Operations Research 19
Countries citing papers authored by David Tolpin
This map shows the geographic impact of David Tolpin'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 Tolpin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Tolpin more than expected).
Fields of papers citing papers by David Tolpin
This network shows the impact of papers produced by David Tolpin. 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 Tolpin. The network helps show where David Tolpin may publish in the future.
Co-authors
The 11 scholars most cited alongside David Tolpin, 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 | 2021 | 51 | |
| 2 | 2016 | 28 | |
| 3 | 2012 | 24 | |
| 4 | 2013 | 8 | |
| 5 | 2017 | 7 | |
| 6 | 2011 | 6 | |
| 7 | 2023 | 3 | |
| 8 | 2021 | 3 | |
| 9 | 2012 | 2 | |
| 10 | 2021 | 2 | |
| 11 | 2021 | 0 |
About David Tolpin
David Tolpin is a scholar working on Artificial Intelligence, Computer Networks and Communications, Management Science and Operations Research, Computational Theory and Mathematics and Control and Systems Engineering, having authored 11 papers that have together received 134 indexed citations. Recurring topics across this work include AI-based Problem Solving and Planning (4 papers), Bayesian Modeling and Causal Inference (4 papers), Advanced Bandit Algorithms Research (4 papers), Artificial Intelligence in Games (3 papers), Advanced Database Systems and Queries (2 papers), Reinforcement Learning in Robotics (2 papers), Constraint Satisfaction and Optimization (2 papers) and Model-Driven Software Engineering Techniques (1 paper). The work is most often cited by research in General Decision Sciences (10 citations), Software (11 citations), Computer Vision and Pattern Recognition (54 citations), Artificial Intelligence (83 citations) and Management Science and Operations Research (19 citations). David Tolpin has collaborated with scholars based in Israel, United Kingdom and United States. Frequent co-authors include Solomon Eyal Shimony, Ariel Felner, Eli Boyarski, Jan-Willem van de Meent, Roni Stern, Hongseok Yang, Frank Wood, Guni Sharon, Stuart Russell and Erez Karpas. Their work appears in journals such as IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics), Artificial Intelligence, Intelligent Decision Technologies, arXiv (Cornell University) and Proceedings of the International Symposium on Combinatorial Search.
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.