Ricardo Gudwin
- Artificial Intelligence top 5%
- Cognitive Neuroscience
- Computer Vision and Pattern Recognition top 10%
- Control and Systems Engineering top 10%
- Computational Theory and Mathematics top 10%
- Co-authors
- Fernando GomideJoão QueirozWitold PedryczFernando J. Von ZubenJônatas ManzolliLeandro Nunes de CastroEric RohmerAlberto J. Álvares
- Topics
- Language and cultural evolution (17 papers)AI-based Problem Solving and Planning (13 papers)Evolutionary Algorithms and Applications (13 papers)
- Journals
- SHILAP Revista de lepidopterologíaFuzzy Sets and SystemsIEEE Transactions on Knowledge and Data Engineering
In The Last Decade
Ricardo Gudwin
72 papers receiving 494 citations
Peers
Comparison fields: 5 of 96
- Artificial Intelligence 270
- Cognitive Neuroscience 90
- Computer Vision and Pattern Recognition 88
- Control and Systems Engineering 87
- Computational Theory and Mathematics 54
Countries citing papers authored by Ricardo Gudwin
This map shows the geographic impact of Ricardo Gudwin'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 Ricardo Gudwin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ricardo Gudwin more than expected).
Fields of papers citing papers by Ricardo Gudwin
This network shows the impact of papers produced by Ricardo Gudwin. 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 Ricardo Gudwin. The network helps show where Ricardo Gudwin may publish in the future.
Co-authorship network of co-authors of Ricardo Gudwin
This figure shows the co-authorship network connecting the top 25 collaborators of Ricardo Gudwin. A scholar is included among the top collaborators of Ricardo Gudwin 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 Ricardo Gudwin. Ricardo Gudwin is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 3 | |
| 3 | 2 | |
| 4 | 2 | |
| 5 | 4 | |
| 6 | 5 | |
| 7 | 0 | |
| 8 | 1 | |
| 9 | 2 | |
| 10 | 7 | |
| 11 | Sign processes in emergence of communication | 1 |
| 12 | 0 | |
| 13 | On the Emergence of Indexical and Symbolic Interpretation in Artificial Creatures, or What is This I Hear? | 3 |
| 14 | A Conscious-based Mind for an Artificial Creature | 2 |
| 15 | 21 | |
| 16 | 39 | |
| 17 | Vox populi: evolutionary for music evolution | 1 |
| 18 | A COMPUTATIONAL TOOL TO MODEL INTELLIGENT SYSTEMS | 3 |
| 19 | Computational Semiotics : An Approach for the Study of Intelligent Systems - Part I : Foundations | 6 |
| 20 | Context Adaptation in Fuzzy Processing | 5 |
About Ricardo Gudwin
Ricardo Gudwin is a scholar working on Cultural Studies, Developmental Biology and Artificial Intelligence, having authored 82 papers that have together received 545 indexed citations. Recurring topics across this work include Language and cultural evolution (17 papers), AI-based Problem Solving and Planning (13 papers) and Evolutionary Algorithms and Applications (13 papers). The work is most often cited by research in Artificial Intelligence (270 citations), Cultural Studies (47 citations) and Signal Processing (52 citations). Ricardo Gudwin has collaborated with scholars based in Brazil, Canada and Sweden. Frequent co-authors include Fernando Gomide, João Queiroz, Witold Pedrycz, Fernando J. Von Zuben, Jônatas Manzolli, Leandro Nunes de Castro, Eric Rohmer, Alberto J. Álvares, Charbel Niño El-Hani and Sidarta Ribeiro. Their work appears in journals such as SHILAP Revista de lepidopterología, Fuzzy Sets and Systems and IEEE Transactions on Knowledge and Data Engineering.
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.