Gregory Kuhlmann

975 citations
10 papers · 424 · h-index 8

Impact in

Papers in

Gregory Kuhlmann

10 papers receiving 366 citations

Peers

Gregory Kuhlmann
Comparison fields: 5 of 60
  • Artificial Intelligence 355
  • Computer Vision and Pattern Recognition 61
  • Management Science and Operations Research 33
  • Computational Theory and Mathematics 38
  • Control and Systems Engineering 49
Replace Avraham Ruderman with:
Avraham Ruderman Australia
Kun Shao China
Matthieu Geist France
Chitra Dadkhah Iran
Shayegan Omidshafiei United States
Harm van Seijen Canada
J. Benton United States
Pradnya Vikhar India
仁 大西
Stasinos Konstantopoulos Greece
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Citations per field
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Citations per year

Countries citing papers authored by Gregory Kuhlmann

Since Specialization
Citations

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

Fields of papers citing papers by Gregory Kuhlmann

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 12 scholars most cited alongside Gregory Kuhlmann, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Gregory Kuhlmann Line = papers co-authored together Gregory Kuhlmann links everyone, so they are left out of the graph.

All Works

10 of 10 papers shown
#Work
1 2005237
2 200864
3
Automatic heuristic construction in a complete general game player
200637
4 200635
5
Know thine enemy: a champion robocup coach agent
200617
6 200611
7
Accelerating Search with Transferred Heuristics
20078
8 20107
9
Transfer Learning and Intelligence: an Argument and Approach
20086
10
Automatic heuristic construction for general game playing
20062

About Gregory Kuhlmann

Gregory Kuhlmann is a scholar working on Artificial Intelligence, Sociology and Political Science, Aerospace Engineering, Biomedical Engineering and Clinical Psychology, having authored 10 papers that have together received 424 indexed citations. Recurring topics across this work include Reinforcement Learning in Robotics (5 papers), Artificial Intelligence in Games (4 papers), Digital Games and Media (2 papers), Robotic Locomotion and Control (2 papers), Robotics and Sensor-Based Localization (2 papers), Marine animal studies overview (1 paper), Adversarial Robustness in Machine Learning (1 paper) and Gambling Behavior and Treatments (1 paper). The work is most often cited by research in Artificial Intelligence (355 citations), Computer Vision and Pattern Recognition (61 citations), Management Science and Operations Research (33 citations), Computational Theory and Mathematics (38 citations) and Control and Systems Engineering (49 citations). Gregory Kuhlmann has collaborated with scholars based in United States and Canada. Frequent co-authors include Peter Stone, Richard S. Sutton, Peter Stone, Matthew E. Taylor, Mohan Sridharan, Kurt Dresner, W. Bradley Knox, Nate Kohl, Nicholas K. Jong and Shilpa Gulati. Their work appears in journals such as Adaptive Behavior, Robotics and Autonomous Systems, Civil War Book Review, Adaptive Agents and Multi-Agents Systems and National Conference on Artificial Intelligence.

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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