James MacGlashan
Impact in
- Artificial Intelligence top 5%
- Reinforcement Learning in Robotics
- Evolutionary Algorithms and Applications
- AI-based Problem Solving and Planning
- Topic Modeling
- Automotive Engineering top 10%
- Autonomous Vehicle Technology and Safety
Papers in
-
- Reinforcement Learning in Robotics 15
- AI-based Problem Solving and Planning 6
- Machine Learning and Algorithms 4
- Evolutionary Algorithms and Applications 3
- Machine Learning and Data Classification 3
- Artificial Intelligence in Games 3
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- Robotic Path Planning Algorithms 3
- Co-authors
- Michael L. Littman (14 shared papers)Marie desJardins (8 shared papers)Stefanie Tellex (7 shared papers)Fiery Andrews Cushman (3 shared papers)Mark K. Ho (3 shared papers)Matthew Edmund Taylor (6 shared papers)David L. Roberts (6 shared papers)Robert Loftin (6 shared papers)
- Journals
- Autonomous Agents and Multi-Agent Systems (1 paper)Cognition (1 paper)Nature (1 paper)JMIR Mental Health (1 paper)IEEE Transactions on Emerging Topics in Computational Intelligence (1 paper)
- Partner nations
- United StatesCanadaFrance
In The Last Decade
James MacGlashan
30 papers receiving 730 citations
James MacGlashan's Hit Papers
Peers
Comparison fields: 5 of 90
- Artificial Intelligence 480
- Automotive Engineering 93
- Control and Systems Engineering 161
- Computer Vision and Pattern Recognition 140
- General Decision Sciences 9
Countries citing papers authored by James MacGlashan
This map shows the geographic impact of James MacGlashan'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 James MacGlashan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites James MacGlashan more than expected).
Fields of papers citing papers by James MacGlashan
This network shows the impact of papers produced by James MacGlashan. 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 James MacGlashan. The network helps show where James MacGlashan may publish in the future.
Co-authors
The 25 scholars most cited alongside James MacGlashan, 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 30 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Outracing champion Gran Turismo drivers with deep reinforcement learning Hit paper breakdown → | 2022 | 256 |
| 2 | 2017 | 57 | |
| 3 | 2015 | 55 | |
| 4 | 2017 | 51 | |
| 5 | 2015 | 49 | |
| 6 | 2014 | 40 | |
| 7 | Showing versus doing: Teaching by demonstration | 2016 | 37 |
| 8 | 2007 | 36 | |
| 9 | 2017 | 35 | |
| 10 | Portable option discovery for automated learning transfer in object-oriented Markov decision processes | 2015 | 22 |
| 11 | 2016 | 20 | |
| 12 | 2014 | 15 | |
| 13 | 2015 | 12 | |
| 14 | 2017 | 12 | |
| 15 | 2018 | 7 | |
| 16 | Learning to interpret natural language instructions | 2012 | 7 |
| 17 | 2010 | 6 | |
| 18 | 2017 | 6 | |
| 19 | Affordances as Transferable Knowledge for Planning Agents. | 2014 | 6 |
| 20 | Minecraft as an Experimental World for AI in Robotics. | 2015 | 5 |
About James MacGlashan
James MacGlashan is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Management Science and Operations Research, Safety Research and Control and Systems Engineering, having authored 30 papers that have together received 765 indexed citations. Recurring topics across this work include Reinforcement Learning in Robotics (15 papers), AI-based Problem Solving and Planning (6 papers), Machine Learning and Algorithms (4 papers), Evolutionary Algorithms and Applications (3 papers), Robotic Path Planning Algorithms (3 papers), Machine Learning and Data Classification (3 papers), Artificial Intelligence in Games (3 papers) and Robot Manipulation and Learning (3 papers). The work is most often cited by research in Artificial Intelligence (480 citations), Automotive Engineering (93 citations), Control and Systems Engineering (161 citations), Computer Vision and Pattern Recognition (140 citations) and General Decision Sciences (9 citations). James MacGlashan has collaborated with scholars based in United States, Canada and France. Frequent co-authors include Michael L. Littman, Marie desJardins, Stefanie Tellex, Fiery Andrews Cushman, Mark K. Ho, Matthew Edmund Taylor, David L. Roberts, Robert Loftin, Bei Peng and Lawson L. S. Wong. Their work appears in journals such as Autonomous Agents and Multi-Agent Systems, Cognition, Nature, JMIR Mental Health and IEEE Transactions on Emerging Topics in Computational 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.