James MacGlashan

1.4k citations
30 papers · 486 · h-index 13

Impact in

    • Reinforcement Learning in Robotics
    • Machine Learning and Algorithms
    • Adversarial Robustness in Machine Learning
    • AI-based Problem Solving and Planning
    • Ethics and Social Impacts of AI

Papers in

    • Reinforcement Learning in Robotics 16
    • AI-based Problem Solving and Planning 5
    • Machine Learning and Algorithms 4
    • Natural Language Processing Techniques 3
    • Evolutionary Algorithms and Applications 3
    • Adversarial Robustness in Machine Learning 3
    • Robotic Path Planning Algorithms 3

James MacGlashan

30 papers receiving 452 citations

Peers

James MacGlashan
Comparison fields: 5 of 70
  • Artificial Intelligence 343
  • Safety Research 53
  • Control and Systems Engineering 108
  • Computer Vision and Pattern Recognition 93
  • General Decision Sciences 7
Replace Jonathan Sorg with:
Jonathan Sorg United States
Sarath Sreedharan United States
Raquel Ros Spain
Matthew Marge United States
Ari Weinstein United States
Amy Isard United Kingdom
Andrea Tacchetti United States
Aurélie Clodic France
Kristinn R. Þórisson Iceland
Agnese Augello Italy
James MacGlashan relative to Jonathan Sorg United States Jonathan Sorg's profile →
Citations per field
00.5×4.0×
Jonathan Sorg · 1×
Citations per year

Countries citing papers authored by James MacGlashan

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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.

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 30 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201747
2 201543
3
Reinforcement Learning as a Framework for Ethical Decision Making
201641
4 201741
5 201740
6 201538
7
Showing versus doing: Teaching by demonstration
201629
8 201429
9 200727
10 201724
11 201616
12
Portable option discovery for automated learning transfer in object-oriented Markov decision processes
201515
13 201414
14
Between imitation and intention learning
201512
15 201710
16 20158
17
Affordances as Transferable Knowledge for Planning Agents.
20145
18
Feature-based Joint Planning and Norm Learning in Collaborative Games.
20165
19 20185
20
Training an Agent to Ground Commands with Reward and Punishment
20145

About James MacGlashan

James MacGlashan is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Control and Systems Engineering, Social Psychology and Safety Research, having authored 30 papers that have together received 486 indexed citations. Recurring topics across this work include Reinforcement Learning in Robotics (16 papers), AI-based Problem Solving and Planning (5 papers), Robot Manipulation and Learning (5 papers), Machine Learning and Algorithms (4 papers), Natural Language Processing Techniques (3 papers), Evolutionary Algorithms and Applications (3 papers), Robotic Path Planning Algorithms (3 papers) and Adversarial Robustness in Machine Learning (3 papers). The work is most often cited by research in Artificial Intelligence (343 citations), Safety Research (53 citations), Control and Systems Engineering (108 citations), Computer Vision and Pattern Recognition (93 citations) and General Decision Sciences (7 citations). James MacGlashan has collaborated with scholars based in United States, Netherlands and France. Frequent co-authors include Michael L. Littman, Marie desJardins, Mark K. Ho, Bei Peng, David L. Roberts, Robert Loftin, Matthew E. Taylor, Stefanie Tellex, Fiery Cushman and David Abel. Their work appears in journals such as Cognition, Proceedings of the National Academy of Sciences, JMIR Mental Health, Autonomous Agents and Multi-Agent Systems 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.

Explore authors with similar magnitude of impact