michalski ryszard (34 Ergebnisse)

gebundene Ausgabe. Zustand: Sehr gut. Zust: Gutes Exemplar. Mit Vorbesitzereintrag auf dem Innentitel. XVI, 456 Seiten, Englisch 930g.

Hardcover. Zustand: Very Good. No Jacket. Missing dust jacket; May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less.

Hardcover. Zustand: Very Good. No Jacket. Missing dust jacket; May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less.

Zustand: Good. Used book that is in clean, average condition without any missing pages.

Zustand: Very Good. 1986th Edition. Former library book; may include library markings. Used book that is in excellent condition. May show signs of wear or have minor defects.

Hardcover. Zustand: Very Good. No Jacket. May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less.

Hardcover. Zustand: Good. No Jacket. Pages can have notes/highlighting. Spine may show signs of wear. ~ ThriftBooks: Read More, Spend Less.

Hardcover. Zustand: Bon. Ancien livre de bibliothèque. Traces d'usure sur la couverture. Edition 1986. Ammareal reverse jusqu'à 15% du prix net de cet article à des organisations caritatives. ENGLISH DESCRIPTION Book Condition: Used, Good. Former library book. Signs of wear on the cover. Edition 1986. Ammareal gives back up to 15% of this item's net price to charity organizations.

24 x 15,5 cm. Zustand: Gut. 1. Auflage. X, 1 Blatt, 738 Seiten Innen sauberer, guter Zustand. Hardcover, Pappeinband, mit den üblichen Bibliotheks-Markierungen, Stempeln und Einträgen, innen wie außen, siehe Bilder. Ecken und Kanten etwas berieben und bestoßen. Oberes Kapital bestoßen. - An Artificial Intelligence Approach, Volume II. RW-SB-01E|A64 Sprache: Englisch Gewicht in Gramm: 1170.

Taschenbuch. Zustand: Neu. Neuware -One of the currently most active research areas within Artificial Intelligence is the field of Machine Learning. which involves the study and development of computational models of learning processes. A major goal of research in this field is to build computers capable of improving their performance with practice and of acquiring knowledge on their own. The intent of this book is to provide a snapshot of this field through a broad. representative set of easily assimilated short papers. As such. this book is intended to complement the two volumes of Machine Learning: An Artificial Intelligence Approach (Morgan-Kaufman Publishers). which provide a smaller number of in-depth research papers. Each of the 77 papers in the present book summarizes a current research effort. and provides references to longer expositions appearing elsewhere. These papers cover a broad range of topics. including research on analogy. conceptual clustering. explanation-based generalization. incremental learning. inductive inference. learning apprentice systems. machine discovery. theoretical models of learning. and applications of machine learning methods. A subject index IS provided to assist in locating research related to specific topics. The majority of these papers were collected from the participants at the Third International Machine Learning Workshop. held June 24-26. 1985 at Skytop Lodge. Skytop. Pennsylvania. While the list of research projects covered is not exhaustive. we believe that it provides a representative sampling of the best ongoing work in the field. and a unique perspective on where the field is and where it is headed.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 448 pp. Englisch.

Hardcover. Zustand: Bon. Ancien livre de bibliothèque avec équipements. Edition 1986. Tome 2. Ammareal reverse jusqu'à 15% du prix net de cet article à des organisations caritatives. ENGLISH DESCRIPTION Book Condition: Used, Good. Former library book. Edition 1986. Volume 2. Ammareal gives back up to 15% of this item's net price to charity organizations.

Gebunden. Zustand: New. Most machine learning research has been concerned with the development of systems that implememnt one type of inference within a single representational paradigm. Such systems, which can be called monostrategy learning systems, include those for.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - Most machine learning research has been concerned with the development of systems that implememnt one type of inference within a single representational paradigm. Such systems, which can be called monostrategy learning systems, include those for empirical induction of decision trees or rules, explanation-based generalization, neural net learning from examples, genetic algorithm-based learning, and others. Monostrategy learning systems can be very effective and useful if learning problems to which they are applied are sufficiently narrowly defined. Many real-world applications, however, pose learning problems that go beyond the capability of monostrategy learning methods. In view of this, recent years have witnessed a growing interest in developing multistrategy systems, which integrate two or more inference types and/or paradigms within one learning system. Such multistrategy systems take advantage of the complementarity of different inference types or representational mechanisms. Therefore, they have a potential to be more versatile and more powerful than monostrategy systems. On the other hand, due to their greater complexity, their development is significantly more difficult and represents a new great challenge to the machine learning community. Multistrategy Learning contains contributions characteristic of the current research in this area.

gebundene Ausgabe. Zustand: Gut. Zust: Gutes Exemplar. Buchkante unten mit Kerben. Mit Vorbesitzereintrag. XI, 782 Seiten, Englisch 1240g.

Pappband. 1983. IX, 572 S. Opp. Buch.

Paperback. Zustand: Brand New. 1st edition. 572 pages. 9.25x6.00x1.32 inches. In Stock.

**Pp. Zustand: Gut. 2. Aufl. 738 Seiten , 1170 g - gutes Exemplar, Einband etwas angestoßen, innen sehr gut (Vorsätze unregelmäßig u. leicht gedunkelt, unkenntlich gemachter Namensstempel (siehe auch mein Foto) [sw.] --- Good condition with normal signs of use gra Sprache: Englisch Gewicht in Gramm: 1170.

Hardcover. Zustand: Befriedigend. 738 Seiten Texteintrag vorne im Buch vorhanden!! Gutes Exemplar, geringe Gebrauchsspuren, Cover/SU berieben/bestoßen, Schnitt/Papier nachgedunkelt, innen alles in Ordnung; Good copy, light signs of previous use, cover/dust jacket shows some rubbing/wear, edges/text pages show yellowing/darkening, interior in good condition B230814ah52 ISBN: 9780934613002 Sprache: Englisch Gewicht in Gramm: 1161.

Gebundene Ausgabe. Zustand: Gut. Exemplar aus einer wissenchaftlichen Bibliothek Sprache: Englisch Gewicht in Gramm: 550.

Hardcover. Zustand: As New. No Jacket. Kluwer Academic Publishers (1986). AsNew Hardcover (Decorated mostly White binding, Black lettering, no dj). New Unused book. 10.25"x7.25"x1.1". be5x.

hardcover. Zustand: Very Good.

hardcover. Zustand: Fine.

hardcover. Zustand: Good. Book is bent.

Zustand: Fair. Acceptable condition. Tutorial #5. Owner's name on front cover. Writing inside. Corners creased. (ai, notes, symposium).

Hardcover. Zustand: Bon. Ancien livre de bibliothèque. Edition 1990. Tome 3. Ammareal reverse jusqu'à 15% du prix net de cet article à des organisations caritatives. ENGLISH DESCRIPTION Book Condition: Used, Good. Former library book. Edition 1990. Volume 3. Ammareal gives back up to 15% of this item's net price to charity organizations.

PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

Gebunden. Zustand: New. One of the currently most active research areas within Artificial Intelligence is the field of Machine Learning. which involves the study and development of computational models of learning processes. A major goal of research in this field is to build compu.

Buch. Zustand: Neu. Neuware - Most machine learning research has been concerned with the development of systems that implememnt one type of inference within a single representational paradigm. Such systems, which can be called monostrategy learning systems, include those for empirical induction of decision trees or rules, explanation-based generalization, neural net learning from examples, genetic algorithm-based learning, and others. Monostrategy learning systems can be very effective and useful if learning problems to which they are applied are sufficiently narrowly defined. Many real-world applications, however, pose learning problems that go beyond the capability of monostrategy learning methods. In view of this, recent years have witnessed a growing interest in developing multistrategy systems, which integrate two or more inference types and/or paradigms within one learning system. Such multistrategy systems take advantage of the complementarity of different inference types or representational mechanisms. Therefore, they have a potential to be more versatile and more powerful than monostrategy systems. On the other hand, due to their greater complexity, their development is significantly more difficult and represents a new great challenge to the machine learning community. Multistrategy Learning contains contributions characteristic of the current research in this area.

Hardcover. Zustand: Very Good. No Jacket. May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less 2.74.

Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - One of the currently most active research areas within Artificial Intelligence is the field of Machine Learning. which involves the study and development of computational models of learning processes. A major goal of research in this field is to build computers capable of improving their performance with practice and of acquiring knowledge on their own. The intent of this book is to provide a snapshot of this field through a broad. representative set of easily assimilated short papers. As such. this book is intended to complement the two volumes of Machine Learning: An Artificial Intelligence Approach (Morgan-Kaufman Publishers). which provide a smaller number of in-depth research papers. Each of the 77 papers in the present book summarizes a current research effort. and provides references to longer expositions appearing elsewhere. These papers cover a broad range of topics. including research on analogy. conceptual clustering. explanation-based generalization. incremental learning. inductive inference. learning apprentice systems. machine discovery. theoretical models of learning. and applications of machine learning methods. A subject index IS provided to assist in locating research related to specific topics. The majority of these papers were collected from the participants at the Third International Machine Learning Workshop. held June 24-26. 1985 at Skytop Lodge. Skytop. Pennsylvania. While the list of research projects covered is not exhaustive. we believe that it provides a representative sampling of the best ongoing work in the field. and a unique perspective on where the field is and where it is headed.