AI-Driven Consensus: Modeling Multi-Agent Networks with Long-Range Interactions Through Path-Laplacian Matrices
Extended connectivity in graphs can be analyzed through <i>k</i>-path Laplacian matrices, which permit the capture of long-range interactions in various real-world networked systems such as social, transportation, and multi-agent networks. In this work, we present several alternative met...
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MDPI AG
2025-05-01
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| author | Yusef Ahsini Belén Reverte J. Alberto Conejero |
| author_facet | Yusef Ahsini Belén Reverte J. Alberto Conejero |
| author_sort | Yusef Ahsini |
| collection | DOAJ |
| description | Extended connectivity in graphs can be analyzed through <i>k</i>-path Laplacian matrices, which permit the capture of long-range interactions in various real-world networked systems such as social, transportation, and multi-agent networks. In this work, we present several alternative methods based on machine learning methods (LSTM, xLSTM, Transformer, XGBoost, and ConvLSTM) to predict the final consensus value based on directed networks (Erdös–Renyi, Watts–Strogatz, and Barabási–Albert) and on the initial state. We highlight how different <i>k</i>-hop interactions affect the performance of the tested methods. This framework opens new avenues for analyzing multi-scale diffusion processes in large-scale, complex networks. |
| format | Article |
| id | doaj-art-e43c8f10a2f14fd49ed69a4a0d6c7975 |
| institution | OA Journals |
| issn | 2076-3417 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj-art-e43c8f10a2f14fd49ed69a4a0d6c79752025-08-20T02:24:47ZengMDPI AGApplied Sciences2076-34172025-05-01159506410.3390/app15095064AI-Driven Consensus: Modeling Multi-Agent Networks with Long-Range Interactions Through Path-Laplacian MatricesYusef Ahsini0Belén Reverte1J. Alberto Conejero2Instituto Universitario Matemática Pura y Aplicada, Universitat Politècnica de València, 46022 València, SpainInstituto Universitario Matemática Pura y Aplicada, Universitat Politècnica de València, 46022 València, SpainInstituto Universitario Matemática Pura y Aplicada, Universitat Politècnica de València, 46022 València, SpainExtended connectivity in graphs can be analyzed through <i>k</i>-path Laplacian matrices, which permit the capture of long-range interactions in various real-world networked systems such as social, transportation, and multi-agent networks. In this work, we present several alternative methods based on machine learning methods (LSTM, xLSTM, Transformer, XGBoost, and ConvLSTM) to predict the final consensus value based on directed networks (Erdös–Renyi, Watts–Strogatz, and Barabási–Albert) and on the initial state. We highlight how different <i>k</i>-hop interactions affect the performance of the tested methods. This framework opens new avenues for analyzing multi-scale diffusion processes in large-scale, complex networks.https://www.mdpi.com/2076-3417/15/9/5064Laplacian matricesnetworks diffusionnetworks consensus |
| spellingShingle | Yusef Ahsini Belén Reverte J. Alberto Conejero AI-Driven Consensus: Modeling Multi-Agent Networks with Long-Range Interactions Through Path-Laplacian Matrices Applied Sciences Laplacian matrices networks diffusion networks consensus |
| title | AI-Driven Consensus: Modeling Multi-Agent Networks with Long-Range Interactions Through Path-Laplacian Matrices |
| title_full | AI-Driven Consensus: Modeling Multi-Agent Networks with Long-Range Interactions Through Path-Laplacian Matrices |
| title_fullStr | AI-Driven Consensus: Modeling Multi-Agent Networks with Long-Range Interactions Through Path-Laplacian Matrices |
| title_full_unstemmed | AI-Driven Consensus: Modeling Multi-Agent Networks with Long-Range Interactions Through Path-Laplacian Matrices |
| title_short | AI-Driven Consensus: Modeling Multi-Agent Networks with Long-Range Interactions Through Path-Laplacian Matrices |
| title_sort | ai driven consensus modeling multi agent networks with long range interactions through path laplacian matrices |
| topic | Laplacian matrices networks diffusion networks consensus |
| url | https://www.mdpi.com/2076-3417/15/9/5064 |
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