Richard Sutton and Andrew Barto provide a clear and simple account of the key ideas and algorithms of reinforcement learning. Their discussion ranges from the history of the field's intellectual foundations to the most recent developments and applications.
"Sinopsis" puede pertenecer a otra edición de este libro.
Richard S. Sutton is Professor of Computing Science and AITF Chair in Reinforcement Learning and Artificial Intelligence at the University of Alberta, and also Distinguished Research Scientist at DeepMind.
Andrew G. Barto is Professor Emeritus in the College of Computer and Information Sciences at the University of Massachusetts Amherst.
"Sobre este título" puede pertenecer a otra edición de este libro.
Librería: BooksRun, Philadelphia, PA, Estados Unidos de America
Hardcover. Condición: Very Good. First Edition. With dust jacket. It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting. Nº de ref. del artículo: 0262193981-11-1-29
Cantidad disponible: 1 disponibles
Librería: More Than Words, Waltham, MA, Estados Unidos de America
Condición: Good. . Good. All orders guaranteed and ship within 24 hours. Before placing your order for please contact us for confirmation on the book's binding. Check out our other listings to add to your order for discounted shipping. Nº de ref. del artículo: WAL-G-4g-002441
Cantidad disponible: 1 disponibles
Librería: World of Books (was SecondSale), Montgomery, IL, Estados Unidos de America
Condición: Acceptable. Item in acceptable condition! Textbooks may not include supplemental items i.e. CDs, access codes etc. Nº de ref. del artículo: 00105534309
Cantidad disponible: 1 disponibles
Librería: HPB-Red, Dallas, TX, Estados Unidos de America
Hardcover. Condición: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority! Nº de ref. del artículo: S_469105041
Cantidad disponible: 1 disponibles
Librería: Goodwill of Silicon Valley, SAN JOSE, CA, Estados Unidos de America
Condición: good. Supports Goodwill of Silicon Valley job training programs. The cover and pages are in Good condition! Any other included accessories are also in Good condition showing use. Use can include some highlighting and writing, page and cover creases as well as other types visible wear. Nº de ref. del artículo: GWSVV.0262193981.G
Cantidad disponible: 2 disponibles
Librería: Better World Books: West, Reno, NV, Estados Unidos de America
Condición: Very Good. Pages intact with possible writing/highlighting. Binding strong with minor wear. Dust jackets/supplements may not be included. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good. Nº de ref. del artículo: 9002566-6
Cantidad disponible: 1 disponibles
Librería: Little Moon Books, San Francisco, CA, Estados Unidos de America
Hardcover. Condición: Very Good. Estado de la sobrecubierta: Very Good. 1st Edition. Hardcover with dust jacket. Interior clean. Light general wear. 322 pages. Nº de ref. del artículo: ABE-1780472090962
Cantidad disponible: 1 disponibles
Librería: Better World Books, Mishawaka, IN, Estados Unidos de America
Condición: Good. Pages intact with minimal writing/highlighting. The binding may be loose and creased. Dust jackets/supplements are not included. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good. Nº de ref. del artículo: GRP14609677
Cantidad disponible: 1 disponibles
Librería: Book Gurus, Tallahassee, FL, Estados Unidos de America
hardcover. Condición: Fine. Nº de ref. del artículo: 01KX3R98ZAXRS3Q
Cantidad disponible: 1 disponibles
Librería: Sekkes Consultants, North Dighton, MA, Estados Unidos de America
Hardcover. Condición: Near fine. Estado de la sobrecubierta: Near fine. One of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives when interacting with a complex, uncertain environment. InReinforcement Learning, Richard Sutton and Andrew Barto provide a clear and simple account of the key ideas and algorithms of reinforcement learning. The only necessary mathematical background is familiarity with elementary concepts of probability. Owner Signature on ffep, fine otherwise. 7¼" - 9¼". Book. Nº de ref. del artículo: 278286
Cantidad disponible: 1 disponibles