Gregor Behnke

975 citations
53 papers · 591 indexed · h-index 15
Topics
AI-based Problem Solving and Planning (42 papers)Logic, Reasoning, and Knowledge (21 papers)Semantic Web and Ontologies (21 papers)
Journals
SHILAP Revista de lepidopterologíaJournal of Artificial Intelligence ResearchAI Magazine

In The Last Decade

Gregor Behnke

50 papers receiving 517 citations

Peers

Gregor Behnke
Comparison fields: 5 of 33
  • Artificial Intelligence 534
  • Computer Networks and Communications 105
  • Computational Theory and Mathematics 91
  • Computer Vision and Pattern Recognition 73
  • Software 73
Replace Daniel Höller with:
Daniel Höller Germany
Ron Alford United States
Martin Wehrle Switzerland
Helen Treharne United Kingdom
Sean McDirmid United States
Abbas K. Zaidi United States
Torbjörn Lager Sweden
Jaime Carbonell United States
Ravi Chugh United States
Marcello M. Bersani Italy
Gregor Behnke relative to Daniel Höller Germany Daniel Höller's profile →
Citations per field
00.5×1.5×
Daniel Höller · 1×
Citations per year

Countries citing papers authored by Gregor Behnke

Since Specialization
Citations

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

Fields of papers citing papers by Gregor Behnke

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Gregor Behnke

This figure shows the co-authorship network connecting the top 25 collaborators of Gregor Behnke. A scholar is included among the top collaborators of Gregor Behnke 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 Gregor Behnke. Gregor Behnke 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
#WorkIndexed citations
1 1
2 1
3 1
4 0
5 2
6 0
7 1
8 2
9 7
10
X and more Parallelism. Integrating LTL-Next into SAT-based Planning with Trajectory Constraints while Allowing for even more Parallelism
5
11 13
12 17
13 5
14 31
15 17
16 2
17 5
18 32
19
Integrating Ontologies and Planning for Cognitive Systems.
5
20 32

About Gregor Behnke

Gregor Behnke is a scholar working on Software, Artificial Intelligence and Computational Theory and Mathematics, having authored 53 papers that have together received 591 indexed citations. Recurring topics across this work include AI-based Problem Solving and Planning (42 papers), Logic, Reasoning, and Knowledge (21 papers) and Semantic Web and Ontologies (21 papers). The work is most often cited by research in Software (73 citations), Artificial Intelligence (534 citations) and Computational Theory and Mathematics (91 citations). Gregor Behnke has collaborated with scholars based in Germany, Australia and Netherlands. Frequent co-authors include Susanne Biundo, Daniel Höller, Pascal Bercher, Ron Alford, Wolfgang Minker, Birte Glimm, Matthias Kraus, Michael Dorna, Roman Barták and David W. Aha. Their work appears in journals such as SHILAP Revista de lepidopterología, Journal of Artificial Intelligence Research and AI Magazine.

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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