Gaya López, María CruzGiráldez Betrón, Juan IgnacioCorchado, EmilioAbraham, AjithPedrycz, Witold2016-07-202016-07-202008Gaya, M. C., & Giraldez, J. I. (2008). Experiments in multi agent learning. In E. Corchado, A. Abraham & W. Pedrycz (Eds.), Third International Workshop on Hybrid Artificial Intelligence Systems: HAIS 2008 (pp. 78-85). Berlin: Springer. DOI: 10.1007/978-3-540-87656-4_1197835408765579783540876564http://hdl.handle.net/11268/5424Data sources are often dispersed geographically in real life applications. Finding a knowledge model may require to join all the data sources and to run a machine learning algorithm on the joint set. We present an alternative based on a Multi Agent System (MAS): an agent mines one data source in order to extract a local theory (knowledge model) and then merges it with the previous MAS theory using a knowledge fusion technique. This way, we obtain a global theory that summarizes the distributed knowledge without spending resources and time in joining data sources. The results show that, as a result of knowledge fusion, the accuracy of initial theories is improved as well as the accuracy of the monolithic solution.engconference output10.1007/978-3-540-87656-4_11restricted accessSistemas de control inteligentesInformática