Llinas james (119 resultados)

Hardcover. Condición: Acceptable. Connecting readers with great books since 1972. Used textbooks may not include companion materials such as access codes, etc. May have condition issues including wear and notes/highlighting. We ship orders daily and Customer Service is our top priority.

Condición: Good. Meets or exceeds the good condition guidelines. Nice copy. Please read before purchase: Has severe spine crack - must be read gently - pages still intact. Five star seller - Buy with confidence.

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.

Hardback. Condición: Very Good. The book has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged.

Hardcover. Condición: Very Good. 1. 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.

Condición: Very Good. Former library copy. Pages intact with possible writing/highlighting. Binding strong with minor wear. Dust jackets/supplements may not be included. Includes library markings. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good.

Condición: New. Satisfaction Guaranteed or your money back.

Condición: Brand New. New.SoftCover International edition. Different ISBN and Cover image but contents are same as US edition.Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.

Condición: New.

Paperback. Condición: New. 1st ed. 2021. Many current AI and machine learning algorithms and data and information fusion processes attempt in software to estimate situations in our complex world of nested feedback loops. Such algorithms and processes must gracefully and efficiently adapt to technical challenges such as data quality induced by these loops, and interdependencies that vary in complexity, space, and time.To realize effective and efficient designs of computational systems, a Systems Engineering perspective may provide a framework for identifying the interrelationships and patterns of change between components rather than static snapshots. We must study cascading interdependencies through this perspective to understand their behavior and to successfully adopt complex system-of-systems in society. This book derives in part from the presentations given at the AAAI 2021 Spring Symposium session on Leveraging Systems Engineering to Realize Synergistic AI / Machine Learning Capabilities. Its 16 chapters offer an emphasis on pragmatic aspects and address topics in systems engineering; AI, machine learning, and reasoning; data and information fusion; intelligent systems; autonomous systems; interdependence and teamwork; human-computer interaction; trust; and resilience.…

Condición: As New. Unread book in perfect condition.

Condición: Bueno. Artech House Publishers, 1990. EN BUEN ESTADO.

Hardcover. Condición: New. In shrink wrap. Looks like an interesting title.

Condición: New.

Condición: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.

Condición: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.

Condición: New. 1st ed. 2021 edition NO-PA16APR2015-KAP.

Paperback. Condición: New. Brand new book, sourced directly from publisher. Dispatch time is 7-8 days from our warehouse. Book will be sent in robust, secure packaging to ensure it reaches you securely.

Condición: New.

Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - Many current AI and machine learning algorithms and data and information fusion processesattempt in software to estimate situations in our complex world of nested feedback loops. Suchalgorithms and processes must gracefully and efficiently adapt to technical challenges such asdata quality induced by these loops, and interdependencies that vary in complexity, space, andtime.To realize effective and efficient designs of computational systems, a Systems Engineeringperspective may provide a framework for identifying the interrelationships and patterns ofchange between components rather than static snapshots. We must study cascadinginterdependencies through this perspective to understand their behavior and to successfullyadopt complex system-of-systems in society.This book derives in part from the presentations given at the AAAI 2021 Spring Symposiumsession on Leveraging Systems Engineering to Realize Synergistic AI / Machine LearningCapabilities. Its 16 chapters offer an emphasis on pragmatic aspects and address topics insystems engineering; AI, machine learning, and reasoning; data and information fusion;intelligent systems; autonomous systems; interdependence and teamwork; human-computerinteraction; trust; and resilience.…

Condición: New. pp. 498.

Condición: Gut. Zustand: Gut | Seiten: 488 | Sprache: Englisch | Produktart: Bücher | Explains numeric and symbolic approaches to data association, tracking combination, classification, and situation assessment, and provides an overview of data fusion theory and mathematical formalisms.

Condición: good. A copy that has been read, remains in good condition. All pages are intact, and the cover is intact. The spine and cover show signs of wear. Pages can include notes and highlighting and show signs of wear, and the copy can include "From the library of" labels or previous owner inscriptions. 100% GUARANTEE! Shipped with delivery confirmation, if you're not satisfied with purchase please return item! Ships via media mail.…

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.

Condición: New. pp. 498.

hardcover. Condición: New. In shrink wrap. Looks like an interesting title.

Condición: New.

Condición: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.

Paperback / softback. Condición: New. New copy - Usually dispatched within 4 working days.

Paperback. Condición: New. 1st ed. 2021. Many current AI and machine learning algorithms and data and information fusion processes attempt in software to estimate situations in our complex world of nested feedback loops. Such algorithms and processes must gracefully and efficiently adapt to technical challenges such as data quality induced by these loops, and interdependencies that vary in complexity, space, and time.To realize effective and efficient designs of computational systems, a Systems Engineering perspective may provide a framework for identifying the interrelationships and patterns of change between components rather than static snapshots. We must study cascading interdependencies through this perspective to understand their behavior and to successfully adopt complex system-of-systems in society. This book derives in part from the presentations given at the AAAI 2021 Spring Symposium session on Leveraging Systems Engineering to Realize Synergistic AI / Machine Learning Capabilities. Its 16 chapters offer an emphasis on pragmatic aspects and address topics in systems engineering; AI, machine learning, and reasoning; data and information fusion; intelligent systems; autonomous systems; interdependence and teamwork; human-computer interaction; trust; and resilience.…