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Nonparametric Bayesian Learning for Collaborative Robot Multimodal Introspection

$58.68 CAD
$59.26 CAD More info
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Shipping options

Seller handling time is 3 business days Details
No shipping price specified to CA
Ships from United States Us

Offer policy

OBO - Seller accepts offers on this item. Details

Return policy

Full refund available within 30 days

Purchase protection

Payment options

PayPal accepted
PayPal Credit accepted
Venmo accepted
PayPal, MasterCard, Visa, Discover, and American Express accepted
Maestro accepted
Amazon Pay accepted
Nuvei accepted

Item traits

Category:

Books

Quantity Available:

Only one in stock, order soon

Condition:

Very Good

Author:

Shuai Li/Juan Rojas/Zhihao Xu/Hongmin Wu/Xuefeng Zhou

Language:

English

Topic:

Electrical/Robotics/Probability & Statistics / Bayesian Analysis

Format:

Hardcover

Publisher:

Springer

Genre:

Mathematics/Technology & Engineering

Publication Year:

2020

Type:

Does not apply

Illustrator:

Yes

Item Length:

9.3 in

Item Weight:

16 Oz

Item Width:

6.1 in

Number of Pages:

Xvii, 137 Pages

Publication Name:

Does not apply

ISBN-13:

9789811562624

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Shipping weights of all items added together for savings.

Posted for sale:

More than a week ago

Item number:

1725260561

Item description

Explore cutting-edge robotic intelligence with Nonparametric Bayesian Learning for Collaborative Robot Multimodal Introspection! This advanced resource delves into machine learning, probabilistic modeling, and multimodal introspection, essential for AI-driven robotics and human-robot collaboration. ? Covers nonparametric Bayesian methods for adaptive robotic learning ? Focuses on multimodal introspection ? sensory fusion and decision-making ? Applications in collaborative robotics ? Enhancing autonomy and interaction ? Ideal for researchers, engineers, and AI enthusiasts in robotics and machine learning ? A must-have reference for cutting-edge developments in AI-powered robots Perfect for professionals and students in robotics, AI, and probabilistic learning, this book offers insights into next-generation autonomous systems. Get your copy today and stay ahead in the field of intelligent robotics! ?