Patrick MacAlpine

33 papers receiving 424 citations

Peers

Patrick MacAlpine
Comparison fields: 5 of 64
  • Artificial Intelligence 264
  • Information Systems and Management 55
  • Computer Vision and Pattern Recognition 132
  • Management Science and Operations Research 77
  • Control and Systems Engineering 103
Replace Francisco Cruz with:
Francisco Cruz Australia
Aurélie Clodic France
Paul E. Nielsen United States
Nakul Gopalan United States
Gianni Vercelli Italy
Jean Botev Luxembourg
Tijn van der Zant Netherlands
Ian Lane United States
Robert Loftin United States
Patrick MacAlpine relative to Francisco Cruz Australia Francisco Cruz's profile →
Citations per field
00.5×2×3×4×4.6×
Francisco Cruz · 1×
Citations per year

Countries citing papers authored by Patrick MacAlpine

Since Specialization
Citations

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

Fields of papers citing papers by Patrick MacAlpine

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 21 scholars most cited alongside Patrick MacAlpine, 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 Patrick MacAlpine Line = papers co-authored together Patrick MacAlpine links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 33 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201846
2 201339
3 201532
4 201127
5 201226
6 201324
7 201524
8 201723
9 201523
10 201322
11 201520
12 201517
13 201415
14 201514
15 201713
16 201812
17
SCRAM: Scalable Collision-avoiding Role Assignment with Minimal-makespan for Formational Positioning
20149
18 20178
19 20128
20 20177

About Patrick MacAlpine

Patrick MacAlpine is a scholar working on Artificial Intelligence, Biomedical Engineering, Management Science and Operations Research, Computer Vision and Pattern Recognition and Control and Systems Engineering, having authored 33 papers that have together received 449 indexed citations. Recurring topics across this work include Reinforcement Learning in Robotics (23 papers), Robotic Locomotion and Control (13 papers), Simulation Techniques and Applications (12 papers), Robotic Path Planning Algorithms (9 papers), Scientific Computing and Data Management (7 papers), Robot Manipulation and Learning (5 papers), Teaching and Learning Programming (5 papers) and Autonomous Vehicle Technology and Safety (2 papers). The work is most often cited by research in Artificial Intelligence (264 citations), Information Systems and Management (55 citations), Computer Vision and Pattern Recognition (132 citations), Management Science and Operations Research (77 citations) and Control and Systems Engineering (103 citations). Patrick MacAlpine has collaborated with scholars based in United States, United Kingdom and China. Frequent co-authors include Peter Stone, Samuel Barrett, Eric Price, Peter Stone, Daniel Urieli, Francisco J. Barrera, Jason Liang, Shivaram Kalyanakrishnan, Justine E. Hoch and Karen E. Adolph. Their work appears in journals such as Lecture notes in computer science, IEEE Intelligent Systems, Frontiers in Neurorobotics, Developmental Science and 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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