Simon McGregor
Impact in
- Cognitive Neuroscience top 10%
- Embodied and Extended Cognition
- Neural dynamics and brain function
- Artificial Intelligence top 10%
- Evolutionary Algorithms and Applications
- Reinforcement Learning in Robotics
Papers in
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- Embodied and Extended Cognition 7
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- Philosophy and History of Science 4
- Co-authors
- Christopher L. Buckley (1 shared paper)Chang Sub Kim (1 shared paper)Anil K. Seth (1 shared paper)Chrisantha Fernando (2 shared papers)Nathaniel Virgo (5 shared papers)Vera Vasas (1 shared paper)Phil Husbands (1 shared paper)Takashi Ikegami (2 shared papers)
- Journals
- Artificial Life (3 papers)Adaptive Behavior (2 papers)Genetic Programming and Evolvable Machines (1 paper)PLoS ONE (1 paper)Neural Networks (1 paper)
- Partner nations
- United KingdomJapanSpain
In The Last Decade
Simon McGregor
21 papers receiving 413 citations
Peers
Comparison fields: 5 of 58
- Cognitive Neuroscience 217
- Artificial Intelligence 102
- Statistical and Nonlinear Physics 32
- History and Philosophy of Science 32
- Computational Theory and Mathematics 36
Countries citing papers authored by Simon McGregor
This map shows the geographic impact of Simon McGregor'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 Simon McGregor with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Simon McGregor more than expected).
Fields of papers citing papers by Simon McGregor
This network shows the impact of papers produced by Simon McGregor. 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 Simon McGregor. The network helps show where Simon McGregor may publish in the future.
Co-authors
The 15 scholars most cited alongside Simon McGregor, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 21 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2017 | 236 | |
| 2 | 2016 | 76 | |
| 3 | 2012 | 47 | |
| 4 | 2016 | 16 | |
| 5 | 2008 | 12 | |
| 6 | 2005 | 11 | |
| 7 | 2011 | 10 | |
| 8 | 2011 | 9 | |
| 9 | 2017 | 9 | |
| 10 | 2021 | 5 | |
| 11 | Algorithmic Information Theory and Novelty Generation | 2007 | 3 |
| 12 | 2005 | 1 | |
| 13 | 2007 | 1 | |
| 14 | 2007 | 1 | |
| 15 | 2014 | 1 | |
| 16 | 2014 | 1 | |
| 17 | 2016 | 1 | |
| 18 | 2017 | 1 | |
| 19 | 2018 | 1 | |
| 20 | 2020 | 1 |
About Simon McGregor
Simon McGregor is a scholar working on Cognitive Neuroscience, History and Philosophy of Science, Statistical and Nonlinear Physics, Artificial Intelligence and Astronomy and Astrophysics, having authored 21 papers that have together received 444 indexed citations. Recurring topics across this work include Embodied and Extended Cognition (7 papers), Philosophy and History of Science (4 papers), Origins and Evolution of Life (3 papers), Complex Systems and Dynamics (3 papers), Neural Networks and Applications (3 papers), Evolutionary Algorithms and Applications (2 papers), Philosophy and Theoretical Science (2 papers) and Computability, Logic, AI Algorithms (2 papers). The work is most often cited by research in Cognitive Neuroscience (217 citations), Artificial Intelligence (102 citations), Statistical and Nonlinear Physics (32 citations), History and Philosophy of Science (32 citations) and Computational Theory and Mathematics (36 citations). Simon McGregor has collaborated with scholars based in United Kingdom, Japan and Spain. Frequent co-authors include Christopher L. Buckley, Chang Sub Kim, Anil K. Seth, Chrisantha Fernando, Nathaniel Virgo, Vera Vasas, Phil Husbands, Takashi Ikegami, Daniel Polani and Kerstin Dautenhahn. Their work appears in journals such as Artificial Life, Adaptive Behavior, Genetic Programming and Evolvable Machines, PLoS ONE and Neural Networks.
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.