Please use this identifier to cite or link to this item: https://hdl.handle.net/10216/67405
Full metadata record
DC FieldValueLanguage
dc.creatorFrancisco Reinaldo
dc.creatorMarcus Siqueira
dc.creatorRui Camacho
dc.creatorLuís Paulo Reis
dc.date.accessioned2019-01-31T10:48:48Z-
dc.date.available2019-01-31T10:48:48Z-
dc.date.issued2006
dc.identifier.othersigarra:64191
dc.identifier.urihttps://repositorio-aberto.up.pt/handle/10216/67405-
dc.description.abstractThis paper presents the AFRANCI tool for the development of Multi-Strategylearning systems. Designing a Multi-Strategy system using AFRANCI is a two step process. The user interactively designs the structure of the system and then chooses the learning strategies for each module. After providing the datasets all modules as automatically trained. The system is aware and takes into consideration the inter-dependency of the modules. The tool has built-inlearning algorithms but can use external programs implementing the learning algorithms.The tool has the following facilities. It allows any user to design in an interactive and easy fashion the structure of the target system. The structure of the target system is a collection of interconnected modules. The user may then choose the different learning algorithms to construct each module. The tool has several built-in Machine Learning algorithms has interfaces that enables it to use external learning tools like WEKA and CN2. AFRANCI uses the interdependency of the modules to determine the sequence of training. For each module the system uses a wrapper to tune automatically the parameters of the learning algorithm. In the final step of the design sequence AFRANCI generates a compact and legible ready-to-use ANSI C open-source code for the final system.To illustrate the concept we have empirically evaluated the tool in the context of the RoboCup Rescue domain. We have developed a small system that uses both neural networks, decision trees and rule induction in the same system. The experiment have shown that a very significant speed up is attained in the development of systems when using this tool.
dc.language.isoeng
dc.relation.ispartof10th WSEAS International Conference on Computers
dc.rightsopenAccess
dc.rights.urihttps://creativecommons.org/licenses/by-nc/4.0/
dc.subjectEngenharia do conhecimento, Engenharia electrotécnica, electrónica e informática
dc.subjectKnowledge engineering, Electrical engineering, Electronic engineering, Information engineering
dc.titleMulti-strategy learning made easy
dc.typeArtigo em Livro de Atas de Conferência Internacional
dc.contributor.uportoFaculdade de Engenharia
dc.subject.fosCiências da engenharia e tecnologias::Engenharia electrotécnica, electrónica e informática
dc.subject.fosEngineering and technology::Electrical engineering, Electronic engineering, Information engineering
Appears in Collections:FEUP - Artigo em Livro de Atas de Conferência Internacional

Files in This Item:
File Description SizeFormat 
64191.pdfMulti-Strategy Learning made easy399.4 kBAdobe PDFThumbnail
View/Open


This item is licensed under a Creative Commons License Creative Commons