Julian Togelius
- Artificial Intelligence top 0.1%
- Artificial Intelligence in Games 200
- Reinforcement Learning in Robotics 55
- Evolutionary Algorithms and Applications 54
- Metaheuristic Optimization Algorithms Research 16
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- Educational Games and Gamification 43
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- Video Analysis and Summarization 48
- Sociology and Political Science top 0.2%
- Digital Games and Media 110
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- Sports Analytics and Performance 18
- Co-authors
- Georgios N. YannakakisSimon M. LucasNoor ShakerAntonios LiapisJürgen SchmidhuberKenneth O. StanleyMark NelsonCameron Browne
- Cited by
- Artificial IntelligenceDevelopmental and Educational PsychologyComputer Vision and Pattern Recognition
- Partner nations
- United StatesDenmarkUnited Kingdom
In The Last Decade
Julian Togelius
272 papers receiving 6.6k citations
Hit Papers
Peers
Comparison fields: 5 of 129
- Artificial Intelligence 5.7k
- Developmental and Educational Psychology 1.5k
- Computer Vision and Pattern Recognition 2.1k
- Computer Graphics and Computer-Aided Design 257
- Sociology and Political Science 3.0k
Countries citing papers authored by Julian Togelius
This map shows the geographic impact of Julian Togelius'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 Julian Togelius with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Julian Togelius more than expected).
Fields of papers citing papers by Julian Togelius
This network shows the impact of papers produced by Julian Togelius. 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 Julian Togelius. The network helps show where Julian Togelius may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Julian Togelius, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2024 | 3 | |
| 2 | 2024 | 13 | |
| 3 | 2024 | 5 | |
| 4 | 2024 | 1 | |
| 5 | 2024 | 1 | |
| 6 | 2023 | 8 | |
| 7 | 2022 | 3 | |
| 8 | 2019 | 14 | |
| 9 | "Superstition" in the Network:Deep Reinforcement Learning Plays Deceptive Games | 2019 | 2 |
| 10 | Blood Bowl: The Next Board Game Challenge for AI | 2018 | 1 |
| 11 | 2018 | 87 | |
| 12 | Depth in strategic games | 2017 | 12 |
| 13 | Procedural Generation of 3D Caves for Games on the GPU | 2015 | 9 |
| 14 | Open Trumps, a Data Game | 2014 | 7 |
| 15 | Detecting Predatory Behaviour in Online Game Chats | 2013 | 1 |
| 16 | Bar Chart Ball, a Data Game | 2013 | 7 |
| 17 | 2013 | 43 | |
| 18 | 2013 | 7 | |
| 19 | 2013 | 40 | |
| 20 | 2011 | 6 |
About Julian Togelius
Julian Togelius is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Developmental and Educational Psychology, having authored 282 papers that have together received 7.0k indexed citations. Recurring topics across this work include Artificial Intelligence in Games (200 papers), Digital Games and Media (110 papers), Reinforcement Learning in Robotics (55 papers), Evolutionary Algorithms and Applications (54 papers), Video Analysis and Summarization (48 papers), Educational Games and Gamification (43 papers), Sports Analytics and Performance (18 papers) and Metaheuristic Optimization Algorithms Research (16 papers). The work is most often cited by research in Artificial Intelligence (5.7k citations), Developmental and Educational Psychology (1.5k citations) and Computer Vision and Pattern Recognition (2.1k citations). Julian Togelius has collaborated with scholars based in United States, Denmark and United Kingdom. Frequent co-authors include Georgios N. Yannakakis, Simon M. Lucas, Noor Shaker, Antonios Liapis, Jürgen Schmidhuber, Kenneth O. Stanley, Mark Nelson, Cameron Browne, Renzo De Nardi and Ahmed Khalifa.
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.