Agent and Multi-Agent Systems: Technologies and Applications: 4th KES International Symposium, KES-AMSTA 2010 Gdynia, Poland, June 23-25, 2010, Proceedings - Couverture souple

Couverture souple

ISBN 10 : 3642135404 ISBN 13 : 9783642135408

Editeur : Springer-Verlag Berlin and Heidelberg GmbH & Co. K, 2010

Synopsis

Presented experiments show that usage ofevolutionary approach to feature - duction is justi?ed.Feature selection as well as construction gives goodresults. It is noticeable that attribute construction s best results assign higher classi?- tion accuracy than feature selection alone.That is why, carrying out selection before construction to decrease searchingspace isagoodsolution. Because of indeterministicbehavior of neuralnetworks, it was di?cultto - ducefeaturesetincaseofusingthemto evaluatecandidateresults.Forexample, aneuralnetworklearntverywellondatathatwasdescribedbyfullattributeset, but when thisset was decreased it had huge problems to do this duringrequired number ofepochs.That suggests that usingC4.5 ismuchmore preferred. Numerous experiments havebeen performed and observed.Analysis ofabove results allowsto put the hypothesisthat it is worth to use Construction module as the feature set reduction. But experiments show that Constructormodule does not work sowell whenitusesthe whole initial set offeatures the search space istoo large.Soit is worth to use ?rstly Selectorand nextConstructor. The second important issue isthatConstructor destructs the semanticmeaning of the features.New constructed features are notunderstandableforusers.In some real-liveproblems measuring offeature values isquite expensive, forsuch problems selector seems to be more suitable because itdiminishes a number of realfeatures.To constructonefeaturesa number ofreal(measured)featurescan be required. Obtainedresults haveencouragedus to extendour system, especiallythe c- structormodule.Weplan to developenlarged set offunctionsFwhich allowsto use the system with data containingdi?erenttype offeatures, not only nume- cal. Such system will be veri?ed usingagreater number ofbenchmark data sets as well as real data. Acknowledgments. This work ispartially ?nanced fromthe Ministryof S- ence and Higher Education Republic of Polandresources in 2008 2010 years as a Poland Singapore joint research project 65/N-SINGAPORE/2007/0."

A propos du livre

Présentation de l'éditeur

This book constitutes the refereed proceedings of the 6th K.E.S. International Conference on Agent and Multi-Agent Systems, K.E.S.-A.M.S.T.A. 2012, held in Dubrovnik, Croatia, in June 2012. The conference attracted a substantial number of researchers and practitioners from all over the world who submitted their papers for ten main tracks covering the methodology and applications of agent and multi-agent systems, one workshop (T.R.U.M.A.S. 2012) and five special sessions on specific topics within the field. The 66 revised papers presented were carefully reviewed and selected for inclusion in the book. The papers are organized in topical sections on virtual organizations, knowledge and learning agents, intelligent workflow, cloud computing and intelligent systems, self-organization, I.C.T.-based alternative and augmentative communication, multi-agent systems, mental and holonic models, assessment methodologies in multi-agent and other paradigms, business processing agents, Trumas 2012 (first international workshop), conversational agents and agent teams, digital economy, and multi-agent systems in distributed environments.

Détails de l'édition

• Éditeur: Springer-Verlag Berlin and Heidelberg GmbH & Co. K
• Date d'édition: 2010
• Langue: anglais
• ISBN 10: 3642135404
• ISBN 13: 9783642135408
• Reliure: Broché
• Nombre de pages: 443
• Éditeur: Jedrzejowicz Piotr, Nguyen Ngoc-Thanh, Howlett Robert J., Jain Lakhmi C
• Coordonnées du fabricant: non disponible
• Personne responsable: CMN Printpool Inh. Mathis Neumann; https://www.also.com/ec/cms5/en_6000/6000/index.jsp; ; Friedrich-Karl-Str. 9; Hamburg; Allemagne