{"id":17487,"date":"2025-10-09T18:03:51","date_gmt":"2025-10-09T16:03:51","guid":{"rendered":"https:\/\/i2cat.net\/?post_type=research-group&p=17487"},"modified":"2025-12-09T13:23:10","modified_gmt":"2025-12-09T12:23:10","slug":"intelligencia-artificial-distribuida","status":"publish","type":"research-group","link":"https:\/\/i2cat.net\/ca\/grup-de-recerca\/intelligencia-artificial-distribuida\/","title":{"rendered":"Intel\u00b7lig\u00e8ncia artificial distribu\u00efda"},"content":{"rendered":"\n
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\n Intel\u00b7lig\u00e8ncia artificial distribu\u00efda<\/p>\n\n

Projectes<\/h2>\n\n <\/div>\n\n
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  • \n\n
    \n \n \"Revolution <\/a>\n \n
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    \n \n Revolution <\/a>\n <\/h3>\n \n \n <\/div>\n\n
    \n <\/span>\n \n Mostra el projecte <\/a>\n <\/div>\n\n <\/div>\n <\/div>\n\n<\/li>\n
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    \n \n \"XReco <\/a>\n \n
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    \n \n XRECO <\/a>\n <\/h3>\n \n \n <\/div>\n\n
    \n <\/span>\n \n Mostra el projecte <\/a>\n <\/div>\n\n <\/div>\n <\/div>\n\n<\/li>\n
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    \n \n \"Teadal <\/a>\n \n
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    \n \n TEADAL <\/a>\n <\/h3>\n \n \n <\/div>\n\n
    \n <\/span>\n \n Mostra el projecte <\/a>\n <\/div>\n\n <\/div>\n <\/div>\n\n<\/li>\n
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    \n \n \"ExtremeXP <\/a>\n \n
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    \n \n EXTREMEXP <\/a>\n <\/h3>\n \n \n <\/div>\n\n
    \n <\/span>\n \n Mostra el projecte <\/a>\n <\/div>\n\n <\/div>\n <\/div>\n\n<\/li>\n
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    \n \n \"DIH4CAT <\/a>\n \n
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    \n \n DIH4CAT <\/a>\n <\/h3>\n \n \n <\/div>\n\n
    \n <\/span>\n \n Mostra el projecte <\/a>\n <\/div>\n\n <\/div>\n <\/div>\n\n<\/li>\n <\/div>\n \n \n \n \n
    \n \n M\u00e9s Projects <\/a>\n
    <\/div>\n
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    \n \n\n\n<\/g>\n<\/svg>\n <\/div>\n\n
    \n \n\n\n<\/g>\n<\/svg>\n <\/div>\n <\/div>\n<\/div> \n \n <\/div>\n\n <\/div>\n<\/section>\n\n\n
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    \n Intel\u00b7lig\u00e8ncia artificial distribu\u00efda<\/p>\n\n

    Publicacions<\/h2>\n\n <\/div>\n\n \n
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    \n \n Predicting alcohol concentration during beer fermentation using ultrasonic measurements and machine learning \n\n<\/svg>\n<\/span>\n <\/a>\n
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    Bowler, Alexander, et al. “Predicting Alcohol Concentration during Beer Fermentation Using Ultrasonic Measurements and Machine Learning.” (2021).<\/p>\n <\/div>\n <\/div>\n\n

    \n \n MTS-GAN: Synthetic Multivariate Time Series Generation with the Mamba Architecture \n\n<\/svg>\n<\/span>\n <\/a>\n
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    Escuder Folch, S., Graupera-Serra, O., Calvo, A., Mu\u00f1oz, B., Guti\u00e9rrez, G., Escrig, J., & Compasti\u00e9, M. (2026). MTS-GAN: Synthetic multivariate time series generation with the Mamba architecture. Knowledge-Based Systems, 115996. https:\/\/doi.org\/10.1016\/j.knosys.2026.115996<\/p>\n <\/div>\n <\/div>\n\n

    \n \n Traffic-aware Multi-Agent Reinforcement Learning-based Distributed Routing for Low Earth Orbit Satellite Network \n\n<\/svg>\n<\/span>\n <\/a>\n
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    Ferrer, E., Escrig, J., Alarc\u00f3n, E., Park, H., Ruiz-De-Azua, J. A., & Kaneko, M. (2026). Traffic-aware Multi-Agent Reinforcement Learning-based Distributed Routing for Low Earth Orbit Satellite Network. IEEE Open Journal of Vehicular Technology.<\/p>\n <\/div>\n <\/div>\n\n

    \n \n Intelligent Sensors for Sustainable Food and Drink Manufacturing \n\n<\/svg>\n<\/span>\n <\/a>\n
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    Watson NJ, Bowler AL, Rady A, Fisher OJ, Simeone A, Escrig J, Woolley E and Adedeji AA (2021) Intelligent Sensors for Sustainable Food and Drink Manufacturing. Front. Sustain. Food Syst. 5:642786. doi: 10.3389\/fsufs.2021.642786<\/p>\n <\/div>\n <\/div>\n\n

    \n \n Interactive digital twins enabling responsible extended reality applications. (Nature, Scientific Reports) \n\n<\/svg>\n<\/span>\n <\/a>\n
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    Antoun, M., Elhajj, I. H., Sayour, M., Papadopoulos, P. K., Zarpalas, D., Rizk, A., Huerta, I., Toledo, L., … & Asmar, D. (2025). Interactive digital twins enabling responsible extended reality applications. Scientific Reports, 15(1), 34539 https:\/\/doi.org\/10.1038\/s41598-025-17855-9<\/p>\n <\/div>\n <\/div>\n\n

    \n \n Considerations, challenges and opportunities when developing data-driven models for process manufacturing systems \n\n<\/svg>\n<\/span>\n <\/a>\n
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    Oliver J Fisher, Nicholas J Watson, Josep E Escrig, Rob Witt, Laura Porcu, Darren Bacon, Martin Rigley, Rachel L Gomes, “Considerations, challenges and opportunities when developing data-driven models for process manufacturing systems”, Computers & Chemical Engineering, Volume 140, 2020. https:\/\/www.sciencedirect.com\/science\/article\/abs\/pii\/S0098135419308373<\/p>\n <\/div>\n <\/div>\n\n \n \n <\/div>\n\n \n\n totes les publicacions \n\n\n<\/g>\n<\/svg>\n <\/a> <\/div>\n<\/section>\n\n\n
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    \n Intel\u00b7lig\u00e8ncia artificial distribu\u00efda<\/p>\n\n

    Novetats recents<\/h2>\n\t<\/div>\n\n\t\t\t
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