Mark Riedl

8.6k citations
199 papers · 5.9k · 3 hit papers · h-index 38

Impact in

Papers in

Mark Riedl

191 papers receiving 5.5k citations

Mark Riedl's Hit Papers

Expanding Explainability: Towards Social Transparency in AI systems 2021 · 350 citations
3500+5+10Years since publication100200300

Peers

Mark Riedl
Comparison fields: 5 of 104
  • Artificial Intelligence 4.2k
  • Human-Computer Interaction 464
  • Computer Graphics and Computer-Aided Design 162
  • Health Informatics 75
  • Safety Research 354
Replace Brian S. Magerko with:
Brian S. Magerko United States
Ana Paiva Portugal
Xiaojuan Ma Hong Kong
Dakuo Wang United States
William Swartout United States
Sherry Tongshuang Wu United States
Johanna D. Moore United Kingdom
Ruth S. Aylett United Kingdom
W. Lewis Johnson United States
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Citations per field
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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 199 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Narrative Planning: Balancing Plot and Character
Hit paper breakdown →
2010390
2
Expanding Explainability: Towards Social Transparency in AI systems
Hit paper breakdown →
2021350
3
Human‐centered artificial intelligence and machine learning
Hit paper breakdown →
2019271
4 2013211
5
An architecture for integrating plan-based behavior generation with interactive game environments.
2004175
6 2003167
7 2019162
8 2006159
9 2020159
10 2013145
11 2004126
12 2018125
13 2019107
14 200695
15 201182
16 202282
17 202179
18 201876
19 202269
20 200964

About Mark Riedl

Mark Riedl is a scholar working on Artificial Intelligence, Computer Graphics and Computer-Aided Design, Computer Science Applications, Human-Computer Interaction and Safety Research, having authored 199 papers that have together received 5.9k indexed citations. Recurring topics across this work include Artificial Intelligence in Games (134 papers), Explainable Artificial Intelligence (XAI) (20 papers), Topic Modeling (17 papers), Reinforcement Learning in Robotics (12 papers), AI-based Problem Solving and Planning (11 papers), Digital Games and Media (10 papers), Ethics and Social Impacts of AI (8 papers) and Digital Media and Visual Art (7 papers). The work is most often cited by research in Artificial Intelligence (4.2k citations), Human-Computer Interaction (464 citations), Computer Graphics and Computer-Aided Design (162 citations), Health Informatics (75 citations) and Safety Research (354 citations). Mark Riedl has collaborated with scholars based in United States, United Kingdom and Austria. Frequent co-authors include R. Michael Young, Upol Ehsan, Brent Harrison, Alexander Zook, Vadim V. Bulitko, Boyang Li, Prithviraj Ammanabrolu, Q. Vera Liao, Matthew Guzdial and Justin D. Weisz. Their work appears in journals such as AI Magazine, Patterns, IEEE Transactions on Computational Intelligence and AI in Games, Proceedings of the ACM on Human-Computer Interaction and Lecture notes in computer science.

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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