9783030107666 - learning automata approach for social networks (studies in computational intelligence, 820, band 820) von rezvanian, alireza; moradabadi, behnaz; ghavipour, mina; daliri khomami, mohammad mehdi; meybodi, mohammad reza (5 Ergebnisse)
Learning Automata Approach for Social Networks (Studies in Computational Intelligence, 820)
Rezvanian, Alireza; Moradabadi, Behnaz; Ghavipour, Mina; Daliri Khomami, Mohammad Mehdi; Meybodi, Mohammad Reza
Sprache: Englisch
Verlag: Springer, 2019
Serie: Buch 325 von 538 - Studies in Computational Intelligence
- Hardcover
Anbieter: Ria Christie Collections, Uxbridge, Vereinigtes KönigreichRia Christie Collections
Verkäufer/-in kontaktierenVerkäufer/-in mit 5 SternenZustand: Neu
EUR 116,68
EUR 14,01 VersandVersand von Vereinigtes Königreich nach USAAnzahl: Mehr als 20 verfügbar
Zustand: New. In.
Sprache: Englisch
Verlag: Springer, 2019
Serie: Buch 325 von 538 - Studies in Computational Intelligence
- Hardcover
Anbieter: Revaluation Books, Exeter, Vereinigtes KönigreichRevaluation Books
Verkäufer/-in kontaktierenVerkäufer/-in mit 5 SternenZustand: Neu
EUR 155,60
EUR 14,62 VersandVersand von Vereinigtes Königreich nach USAAnzahl: 2 verfügbar
Hardcover. Zustand: Brand New. 329 pages. 9.50x6.25x0.75 inches. In Stock.
Sprache: Englisch
Verlag: Springer, 2019
Serie: Buch 325 von 538 - Studies in Computational Intelligence
- Hardcover
Anbieter: Kennys Bookstore, Olney, MD, USAKennys Bookstore
Verkäufer/-in kontaktierenVerkäufer/-in mit 5 SternenZustand: Neu
EUR 163,59
EUR 9,07 VersandVersand innerhalb von USAAnzahl: 15 verfügbar
Zustand: New.
Sprache: Englisch
Verlag: Springer, 2019
Serie: Buch 325 von 538 - Studies in Computational Intelligence
- Hardcover
Anbieter: AHA-BUCH GmbH, Einbeck, DeutschlandAHA-BUCH GmbH
Verkäufer/-in kontaktierenVerkäufer/-in mit 5 SternenZustand: Neu
EUR 111,53
EUR 63,44 VersandVersand von Deutschland nach USAAnzahl: 1 verfügbar
Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book begins by briefly explaining learning automata (LA) models and a recently developed cellular learning automaton (CLA) named wavefront CLA. Analyzing social networks is increasingly important, so as to identify behavioral patterns in interactions a…mong individuals and in the networks' evolution, and to develop the algorithms required for meaningful analysis.As an emerging artificial intelligence research area, learning automata (LA) has already had a significant impact in many areas of social networks. Here, the research areas related to learning and social networks are addressed from bibliometric and network analysis perspectives. In turn, the second part of the book highlights a range of LA-based applications addressing social network problems, from network sampling, community detection, link prediction, and trust management, to recommender systems and finally influence maximization. Given its scope, the book offers a valuable guide for all researchers whose work involves reinforcement learning, social networks and/or artificial intelligence.
Sprache: Englisch
Verlag: Palgrave Macmillan, 2019
Serie: Buch 325 von 538 - Studies in Computational Intelligence
- Hardcover
Anbieter: Buchpark, Trebbin, DeutschlandBuchpark
Verkäufer/-in kontaktierenVerkäufer/-in mit 5 SternenZustand: Gebraucht - Sehr gut
EUR 88,36
EUR 105,00 VersandVersand von Deutschland nach USAAnzahl: 1 verfügbar
Zustand: Sehr gut. Zustand: Sehr gut | Seiten: 348 | Sprache: Englisch | Produktart: Bücher | This book begins by briefly explaining learning automata (LA) models and a recently developed cellular learning automaton (CLA) named wavefront CLA. Analyzing social networks is increasingly important, so as to identify behavioral patte…rns in interactions among individuals and in the networks¿ evolution, and to develop the algorithms required for meaningful analysis. As an emerging artificial intelligence research area, learning automata (LA) has already had a significant impact in many areas of social networks. Here, the research areas related to learning and social networks are addressed from bibliometric and network analysis perspectives. In turn, the second part of the book highlights a range of LA-based applications addressing social network problems, from network sampling, community detection, link prediction, and trust management, to recommender systems and finally influence maximization. Given its scope, the book offers a valuable guide for all researchers whose work involves reinforcement learning, social networks and/or artificial intelligence.
