Hm schwartz (11 Ergebnisse)

Zustand: Good. This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. In good all round condition. Dust jacket in good condition. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,450grams, ISBN:0241892880.…

Zustand: Good. This is an ex-library book and may have the usual library/used-book markings inside.This book has soft covers. Clean from markings. In good all round condition. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,650grams, ISBN:9780333802632. …

Zustand: Poor. This is an ex-library book and may have the usual library/used-book markings inside.This book has soft covers. Clean from markings. In poor condition, suitable as a reading copy. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,600grams, ISBN:9780333618523.…

Zustand: Good. This is an ex-library book and may have the usual library/used-book markings inside.This book has soft covers. In good all round condition. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,700grams, ISBN:9780230521285.

Zustand: as new. Livraison rapide, bien emballé, service client soigné.Pour tout renseignement complémentaire, n'hésitez pas à nous contacter.

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

Zustand: New. pp. 350.

Zustand: New. In English.

Hardcover. Zustand: Brand New. 1st edition. 256 pages. 9.50x6.50x0.75 inches. In Stock.

Zustand: New. Howard M. Schwartz, PhD, received his B.Eng. Degree from McGill University, Montreal, Canada in une 1981 and his MS Degree and PhD Degree from MIT, Cambridge, USA in 1982 and 1987 respectively. He is currently a professor in systems and computer engineering.

Zustand: New. The book begins with a chapter on traditional methods of supervised learning, covering recursive least squares learning, mean square error methods, and stochastic approximation. Chapter 2 covers single agent reinforcement learning. Topics include learning value functions, Markov games, and TD learning with eligibility traces. Num Pages: 256 pages, illustrations. BIC Classification: UYQM. Category: (P) Professional & Vocational. Dimension: 163 x 238 x 18. Weight in Grams: 478. . 2014. 1st Edition. Hardcover. . . . . Books ship from the US and Ireland. …