Mark Riedl

7.5k citations
157 papers · 3.2k · h-index 30

Impact in

Papers in

Mark Riedl

152 papers receiving 3.0k citations

Peers

Mark Riedl
Comparison fields: 5 of 115
  • Health Informatics 118
  • Artificial Intelligence 2.5k
  • Human-Computer Interaction 218
  • Computer Vision and Pattern Recognition 807
  • Developmental and Educational Psychology 484
Replace Antonios Liapis with:
Antonios Liapis Malta
Brian Magerko United States
Michael Terry Canada
Xiaojuan Ma Hong Kong
Saleema Amershi United States
Carrie J. Cai United States
Dakuo Wang United States
Johanna D. Moore United Kingdom
Pascale Fung Hong Kong
W. Lewis Johnson United States
Mark Riedl relative to Antonios Liapis Malta Antonios Liapis's profile →
Citations per field
00.5×10×16×
Antonios Liapis · 1×
Citations per year

Countries citing papers authored by Mark Riedl

Since Specialization
Citations

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

Fields of papers citing papers by Mark Riedl

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Mark Riedl, 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 Mark Riedl Line = papers co-authored together Mark Riedl links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 157 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2010305
2 2013157
3
An architecture for integrating plan-based behavior generation with interactive game environments.
2004129
4 2019126
5 2003109
6 2013108
7 2018106
8 2006104
9 200497
10 201167
11 202260
12 201860
13 202159
14 202252
15 200949
16 201244
17 201744
18 201944
19 201243
20 200641

About Mark Riedl

Mark Riedl is a scholar working on Artificial Intelligence, Sociology and Political Science, Computer Vision and Pattern Recognition, Control and Systems Engineering and Developmental and Educational Psychology, having authored 157 papers that have together received 3.2k indexed citations. Recurring topics across this work include Artificial Intelligence in Games (96 papers), Digital Games and Media (46 papers), Topic Modeling (32 papers), Human Motion and Animation (28 papers), Educational Games and Gamification (23 papers), Video Analysis and Summarization (19 papers), Reinforcement Learning in Robotics (18 papers) and Natural Language Processing Techniques (17 papers). The work is most often cited by research in Health Informatics (118 citations), Artificial Intelligence (2.5k citations), Human-Computer Interaction (218 citations), Computer Vision and Pattern Recognition (807 citations) and Developmental and Educational Psychology (484 citations). Mark Riedl has collaborated with scholars based in United States, Germany and Canada. Frequent co-authors include R. Michael Young, Alexander Zook, Brent Harrison, Vadim Bulitko, Upol Ehsan, Boyang Li, Prithviraj Ammanabrolu, Stephen Lee-Urban, Matthew Guzdial and Larry Chan. Their work appears in journals such as Proceedings of the ACM on Human-Computer Interaction, IEEE Transactions on Computational Intelligence and AI in Games, Patterns, AI Magazine and IEEE Transactions on Cognitive and Developmental Systems.

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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