José Font

453 citations
25 papers · 199 · h-index 8

Impact in

Papers in

José Font

22 papers receiving 189 citations

Peers

José Font
Comparison fields: 5 of 40
  • Artificial Intelligence 152
  • Human-Computer Interaction 25
  • Developmental and Educational Psychology 53
  • Computer Vision and Pattern Recognition 59
  • Computer Graphics and Computer-Aided Design 9
Replace Ben Samuel with:
Ben Samuel United States
Adam Summerville United States
Federico Peinado Spain
Erin J. Hastings United States
Amy K. Hoover United States
Stephen Lee-Urban United States
Ulrike Spierling Germany
Nektarios Moumoutzis Greece
Steve Dahlskog Sweden
Marc Ponsen Netherlands
José Font relative to Ben Samuel United States Ben Samuel's profile →
Citations per field
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Citations per year

Countries citing papers authored by José Font

Since Specialization
Citations

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

Fields of papers citing papers by José Font

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 14 scholars most cited alongside José Font, 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 José Font Line = papers co-authored together José Font links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 25 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201740
2 201825
3 201721
4 202018
5 201815
6 201011
7
Towards the automatic generation of card games through Grammar-Guided Genetic Programming
20139
8 20227
9 20187
10 20225
11 20225
12 20215
13 20124
14 20214
15 20224
16 20173
17 20203
18 20103
19 20102
20 20222

About José Font

José Font is a scholar working on Artificial Intelligence, Sociology and Political Science, Developmental and Educational Psychology, Computer Vision and Pattern Recognition and Molecular Biology, having authored 25 papers that have together received 199 indexed citations. Recurring topics across this work include Artificial Intelligence in Games (13 papers), Digital Games and Media (11 papers), Evolutionary Algorithms and Applications (7 papers), Educational Games and Gamification (6 papers), Metaheuristic Optimization Algorithms Research (4 papers), Gene Regulatory Network Analysis (4 papers), Human Motion and Animation (3 papers) and Innovative Human-Technology Interaction (2 papers). The work is most often cited by research in Artificial Intelligence (152 citations), Human-Computer Interaction (25 citations), Developmental and Educational Psychology (53 citations), Computer Vision and Pattern Recognition (59 citations) and Computer Graphics and Computer-Aided Design (9 citations). José Font has collaborated with scholars based in Sweden, Spain and United States. Frequent co-authors include Steve Dahlskog, Johan Holmberg, Julian Togelius, Daniel Manrique, Simon Johansson, Patrik Nilsson, Tobias Mahlmann, Genoveva López, David del Río and Fernando Alonso. Their work appears in journals such as Applied Soft Computing, Natural Computing, Soft Computing, Expert Systems with Applications and IEEE Transactions on Games.

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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