Oliver G. Selfridge
- Artificial Intelligence top 5%
- Cognitive Neuroscience top 10%
- Computer Vision and Pattern Recognition top 10%
- Control and Systems Engineering
- Computational Theory and Mathematics top 10%
- Co-authors
- Michael A. ArbibEdwina L. RisslandAndrew G. BartoRichard S. SuttonEdward E. DavidMargaret MinskyPamela McCorduckJudy A. Franklin
- Topics
- Reinforcement Learning in Robotics (3 papers)Advanced Control Systems Optimization (1 paper)Optimization and Search Problems (1 paper)
- Partner nations
- United States
In The Last Decade
Oliver G. Selfridge
15 papers receiving 497 citations
Peers
Comparison fields: 5 of 105
- Artificial Intelligence 285
- Cognitive Neuroscience 148
- Computer Vision and Pattern Recognition 88
- Control and Systems Engineering 55
- Computational Theory and Mathematics 55
Countries citing papers authored by Oliver G. Selfridge
This map shows the geographic impact of Oliver G. Selfridge'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 Oliver G. Selfridge with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Oliver G. Selfridge more than expected).
Fields of papers citing papers by Oliver G. Selfridge
This network shows the impact of papers produced by Oliver G. Selfridge. 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 Oliver G. Selfridge. The network helps show where Oliver G. Selfridge may publish in the future.
Co-authorship network of co-authors of Oliver G. Selfridge
This figure shows the co-authorship network connecting the top 25 collaborators of Oliver G. Selfridge. A scholar is included among the top collaborators of Oliver G. Selfridge 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 Oliver G. Selfridge. Oliver G. Selfridge is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 2 | |
| 3 | 15 | |
| 4 | 2 | |
| 5 | 8 | |
| 6 | Pandemonium: a paradigm for learning | 257 |
| 7 | 76 | |
| 8 | 109 | |
| 9 | History of artificial intelligence | 21 |
| 10 | 18 | |
| 11 | 7 | |
| 12 | 5 | |
| 13 | 7 | |
| 14 | 73 | |
| 15 | JAMMING TESTS ON NOMAC SYSTEMS | 1 |
About Oliver G. Selfridge
Oliver G. Selfridge is a scholar working on Computer Science Applications, Human-Computer Interaction and Artificial Intelligence, having authored 15 papers that have together received 603 indexed citations. Recurring topics across this work include Reinforcement Learning in Robotics (3 papers), Advanced Control Systems Optimization (1 paper) and Optimization and Search Problems (1 paper). The work is most often cited by research in Artificial Intelligence (285 citations), Cognitive Neuroscience (148 citations) and Computer Vision and Pattern Recognition (88 citations). Oliver G. Selfridge has collaborated with scholars based in United States. Frequent co-authors include Michael A. Arbib, Edwina L. Rissland, Andrew G. Barto, Richard S. Sutton, Edward E. David, Margaret Minsky, Pamela McCorduck, Judy A. Franklin, Herbert A. Simon and Ulric Neisser. Their work appears in journals such as Scientific American, IEEE Intelligent Systems 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.