Luigi Cardamone
- Artificial Intelligence top 5%
- Automotive Engineering top 5%
- Computer Vision and Pattern Recognition top 10%
- Sociology and Political Science
- Control and Systems Engineering top 10%
- Co-authors
- Daniele LoiaconoPier Luca LanziEnrique OnievaMartin V. ButzDavid A. PeltaDiego Pérez-LiébanaJulian TogeliusMike Preuß
- Topics
- Artificial Intelligence in Games (15 papers)Reinforcement Learning in Robotics (9 papers)Evolutionary Algorithms and Applications (6 papers)
- Journals
- Expert Systems with ApplicationsApplied Soft ComputingIEEE Transactions on Computational Intelligence and AI in Games
- Partner nations
- ItalySpainUnited States
In The Last Decade
Luigi Cardamone
16 papers receiving 450 citations
Peers
Comparison fields: 5 of 44
- Artificial Intelligence 383
- Automotive Engineering 135
- Computer Vision and Pattern Recognition 116
- Sociology and Political Science 103
- Control and Systems Engineering 93
Countries citing papers authored by Luigi Cardamone
This map shows the geographic impact of Luigi Cardamone'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 Luigi Cardamone with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Luigi Cardamone more than expected).
Fields of papers citing papers by Luigi Cardamone
This network shows the impact of papers produced by Luigi Cardamone. 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 Luigi Cardamone. The network helps show where Luigi Cardamone may publish in the future.
Co-authorship network of co-authors of Luigi Cardamone
This figure shows the co-authorship network connecting the top 25 collaborators of Luigi Cardamone. A scholar is included among the top collaborators of Luigi Cardamone 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 Luigi Cardamone. Luigi Cardamone is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 15 | |
| 2 | 4 | |
| 3 | Evolutionary Learning and Search-Based Content Generation in Computer Games | 2 |
| 4 | 16 | |
| 5 | 43 | |
| 6 | 60 | |
| 7 | 11 | |
| 8 | 0 | |
| 9 | 14 | |
| 10 | 16 | |
| 11 | 34 | |
| 12 | 15 | |
| 13 | 70 | |
| 14 | 57 | |
| 15 | 35 | |
| 16 | 38 | |
| 17 | 40 |
About Luigi Cardamone
Luigi Cardamone is a scholar working on Artificial Intelligence, Developmental and Educational Psychology and Computer Graphics and Computer-Aided Design, having authored 17 papers that have together received 470 indexed citations. Recurring topics across this work include Artificial Intelligence in Games (15 papers), Reinforcement Learning in Robotics (9 papers) and Evolutionary Algorithms and Applications (6 papers). The work is most often cited by research in Artificial Intelligence (383 citations), Automotive Engineering (135 citations) and Computer Vision and Pattern Recognition (116 citations). Luigi Cardamone has collaborated with scholars based in Italy, Spain and United States. Frequent co-authors include Daniele Loiacono, Pier Luca Lanzi, Enrique Onieva, Martin V. Butz, David A. Pelta, Diego Pérez-Liébana, Julian Togelius, Mike Preuß, Yago Sáez and Andrea Mocci. Their work appears in journals such as Expert Systems with Applications, Applied Soft Computing and IEEE Transactions on Computational Intelligence and AI in 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.