Please use this identifier to cite or link to this item: https://hdl.handle.net/1822/120

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dc.contributor.authorRocha, Miguel-
dc.contributor.authorCortez, Paulo-
dc.contributor.authorNeves, José-
dc.date.accessioned2003-10-27T18:49:59Z-
dc.date.available2003-10-27T18:49:59Z-
dc.date.issued2003-04-
dc.identifier.citationIn M. Verleysen Ed., Proceedings of 11th European Symposium on Artificial Neural Networks (ESANN'2003), Bruges, Belgium, pp. 487-492eng
dc.identifier.urihttps://hdl.handle.net/1822/120-
dc.description.abstractThe remarkable adaptation of living creatures to their environments comes as a result of the interaction of two orthogonal processes: evolution and learning. Within the Machine Learning arena, both mechanisms inspired the development of the Evolutionary and Connectionist Computation fields, which can be combined under two different views, the Lamarckian and Baldwinian approaches. Comparative tests reward the latter when changing environments are considered.eng
dc.language.isoeng-
dc.publisherd-side publishingeng
dc.rightsopenAccesseng
dc.subjectBaldwin Effecteng
dc.subjectEvolutionary Programmingeng
dc.subjectHybrid Systemseng
dc.subjectLamarckian Optimizationeng
dc.subjectMulti-Layer Perceptronseng
dc.titleAdaptive learning in changing environmentseng
dc.typeconferencePapereng
dc.peerreviewedyeseng
Appears in Collections:CAlg - Artigos em livros de atas/Papers in proceedings
DI/CCTC - Artigos (papers)
DSI - Engenharia da Programação e dos Sistemas Informáticos

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