Mark Riedl

7.5k total citations
157 papers, 3.2k citations indexed

About

Mark Riedl is a scholar working on Artificial Intelligence, Sociology and Political Science and Computer Vision and Pattern Recognition. According to data from OpenAlex, Mark Riedl has authored 157 papers receiving a total of 3.2k indexed citations (citations by other indexed papers that have themselves been cited), including 136 papers in Artificial Intelligence, 48 papers in Sociology and Political Science and 37 papers in Computer Vision and Pattern Recognition. Recurrent topics in Mark Riedl's work include Artificial Intelligence in Games (96 papers), Digital Games and Media (46 papers) and Topic Modeling (32 papers). Mark Riedl is often cited by papers focused on Artificial Intelligence in Games (96 papers), Digital Games and Media (46 papers) and Topic Modeling (32 papers). Mark Riedl collaborates with scholars based in United States, Austria and Germany. Mark Riedl's co-authors include R. Michael Young, Alexander Zook, Brent Harrison, Vadim Bulitko, Upol Ehsan, Boyang Li, Prithviraj Ammanabrolu, Stephen Lee-Urban, Larry Chan and Matthew Guzdial and has published in prestigious journals such as Communications of the ACM, Journal of the Neurological Sciences and International Journal of Human-Computer Studies.

In The Last Decade

Mark Riedl

152 papers receiving 3.0k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Mark Riedl United States 30 2.5k 877 807 484 406 157 3.2k
Michael Mateas United States 36 3.1k 1.3× 2.2k 2.5× 1.2k 1.5× 1.1k 2.3× 532 1.3× 218 4.7k
Antonios Liapis Malta 21 1.1k 0.5× 613 0.7× 468 0.6× 349 0.7× 117 0.3× 119 1.6k
Brian Magerko United States 24 789 0.3× 373 0.4× 345 0.4× 540 1.1× 194 0.5× 132 2.8k
David Traum United States 36 3.5k 1.4× 199 0.2× 334 0.4× 526 1.1× 297 0.7× 223 5.0k
Magy Seif El‐Nasr United States 26 816 0.3× 884 1.0× 576 0.7× 733 1.5× 140 0.3× 146 2.6k
Ruth Aylett United Kingdom 21 776 0.3× 350 0.4× 277 0.3× 240 0.5× 297 0.7× 147 1.7k
Xiaojuan Ma Hong Kong 28 973 0.4× 419 0.5× 635 0.8× 132 0.3× 88 0.2× 196 2.9k
Martha E. Pollack United States 33 2.9k 1.2× 201 0.2× 641 0.8× 124 0.3× 267 0.7× 114 5.0k
R. Michael Young United States 25 1.7k 0.7× 696 0.8× 1.1k 1.3× 262 0.5× 418 1.0× 133 2.6k
W. Lewis Johnson United States 31 2.1k 0.9× 245 0.3× 314 0.4× 873 1.8× 475 1.2× 103 3.6k

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-authorship network of co-authors of Mark Riedl

This figure shows the co-authorship network connecting the top 25 collaborators of Mark Riedl. A scholar is included among the top collaborators of Mark Riedl based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Mark Riedl. Mark Riedl is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Ehsan, Upol, Samir Passi, Q. Vera Liao, et al.. (2024). The Who in XAI: How AI Background Shapes Perceptions of AI Explanations. 1–32. 26 indexed citations
2.
Ehsan, Upol, Q. Vera Liao, Samir Passi, Mark Riedl, & Hal Daumé. (2024). Seamful XAI: Operationalizing Seamful Design in Explainable AI. Proceedings of the ACM on Human-Computer Interaction. 8(CSCW1). 1–29. 5 indexed citations
3.
Ehsan, Upol, Elizabeth Anne Watkins, Philipp Wintersberger, et al.. (2024). Human-Centered Explainable AI (HCXAI): Reloading Explainability in the Era of Large Language Models (LLMs). VBN Forskningsportal (Aalborg Universitet). 1–6. 8 indexed citations
4.
Riedl, Mark, et al.. (2024). Training Value-Aligned Reinforcement Learning Agents Using a Normative Prior. IEEE Transactions on Artificial Intelligence. 5(7). 3350–3361. 1 indexed citations
5.
Ehsan, Upol, Koustuv Saha, Munmun De Choudhury, & Mark Riedl. (2023). Charting the Sociotechnical Gap in Explainable AI: A Framework to Address the Gap in XAI. Proceedings of the ACM on Human-Computer Interaction. 7(CSCW1). 1–32. 35 indexed citations
6.
Ehsan, Upol, Philipp Wintersberger, Elizabeth Anne Watkins, et al.. (2023). Human-Centered Explainable AI (HCXAI): Coming of Age. 1–7. 14 indexed citations
7.
Riedl, Mark & Brent Harrison. (2017). Enter the Matrix: A Virtual World Approach to Safely Interruptable Autonomous Systems.. arXiv (Cornell University). 2 indexed citations
8.
Guzdial, Matthew, Jonathan H. Chen, Shaoyu Chen, & Mark Riedl. (2017). A General Level Design Editor for Co-Creative Level Design. Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment. 13(2). 81–83. 5 indexed citations
9.
Harrison, Brent, et al.. (2017). Toward Automated Story Generation with Markov Chain Monte Carlo Methods and Deep Neural Networks. Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment. 13(2). 191–197. 14 indexed citations
10.
Harrison, Brent & Mark Riedl. (2016). Learning From Stories: Using Crowdsourced Narratives to Train Virtual Agents. Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment. 12(1). 183–189. 4 indexed citations
11.
Harrison, Brent & Mark Riedl. (2016). Towards Learning From Stories: An Approach to Interactive Machine Learning.. National Conference on Artificial Intelligence. 3 indexed citations
12.
Summerville, Adam, et al.. (2016). Learning Player Tailored Content From Observation: Platformer Level Generation from Video Traces using LSTMs. Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment. 12(2). 107–113. 18 indexed citations
13.
Hodhod, Rania, et al.. (2014). Toward Generating 3D Games with the Help of Commonsense Knowledge and the Crowd. Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment. 10(3). 21–27. 2 indexed citations
14.
Li, Boyang, Stephen Lee-Urban, & Mark Riedl. (2012). Toward Autonomous Crowd-Powered Creation of Interactive Narratives. Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment. 8(2). 20–25. 9 indexed citations
15.
Si, Mei, Stacy Marsella, & Mark Riedl. (2008). Interactive Drama Authoring with Plot and Character: An Intelligent System that Fosters Creativity.. National Conference on Artificial Intelligence. 75–81. 3 indexed citations
16.
Si, Mei, Stacy Marsella, & Mark Riedl. (2008). Integrating Story-Centric and Character-Centric Processes for Authoring Interactive Drama. Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment. 4(1). 203–208. 7 indexed citations
17.
Elson, David K. & Mark Riedl. (2007). A Lightweight Intelligent Virtual Cinematography System for Machinima Production. Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment. 3(1). 8–13. 5 indexed citations
18.
Magerko, Brian & Mark Riedl. (2007). Intelligent narrative technologies : Papers from the AAAI Fall Symposium. 2 indexed citations
19.
Riedl, Mark & R. Michael Young. (2005). Open-world planning for story generation. International Joint Conference on Artificial Intelligence. 72(21). 1719–1720. 21 indexed citations
20.
Lent, Michael van, et al.. (2005). Increasing Replayability with Deliberative and Reactive Planning. Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment. 1(1). 135–140. 6 indexed citations

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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