Rare Book
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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.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Paperback. Etat : new. Paperback. 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, aneuralnetworklearntverywellondatathatwasdescribedbyfullattribut eset, 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. Constitutes the proceedings of the 4th KES International Symposium on Agent and Multi-Agent Systems, KES-AMSTA 2010, held in June 2010 in Gdynia, Poland. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N° de réf. du vendeur 9783642135408
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Paperback. Etat : Brand New. 443 pages. 9.25x6.25x1.00 inches. In Stock. N° de réf. du vendeur x-3642135404
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Etat : Sehr gut. Zustand: Sehr gut - Neubindung, Buchrücken leicht angestoßen und eingerissen, Auflage 2010 | Seiten: 443 | Sprache: Englisch | Produktart: Bücher. N° de réf. du vendeur 7839595/12
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Taschenbuch. Etat : Neu. Neuware - 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, aneuralnetworklearntverywellondatathatwasdescribedbyfullattribute set, 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. N° de réf. du vendeur 9783642135408
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Etat : New. Nice bookWell doneGood to haveManagement and e-Business.- Agent-Based Decision Making in the Electronic Marketplace: Interactive Negotiation.- Modeling and Verifying Business Interactions via Commitments and Dialogue Actions.- Personalized Support for M. N° de réf. du vendeur 5050224
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