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سعر ومواصفات Robot Learning from Human Demonstration

  • أفضل سعر لـ Robot Learning from Human Demonstration by جوميا فى مصر هو 390 ج.م.
  • طرق الدفع المتاحة هى
    دفع عند الاستلامبطاقة ائتمانيةالدفع الاليكترونى
  • تكلفة التوصيل هى 15 ج.م., والتوصيل فى خلال 2-5 أيام
  • تباع المنتجات المماثلة لـ Robot Learning from Human Demonstration فى جوميا, نون مع اسعار تبدأ من 416 ج.م.
  • أول ظهور لهذا المنتج كان فى يوليو 01, 2017
  • من بين المنتجات المماثلة لـ Robot Learning from Human Demonstration أرخص سعر هو 366 ج.م. من نون

المواصفات الفنية

SKU:JU030BK16PL5WNAFAMZ
المؤلف:Thomaz
الموديل:9781627051996

منتجات مماثلة

متجر

طرق الدفع

مدة التوصيل

تكلفة التوصيل

وصف جوميا

  • Paperback ‎- Number of Pages‎:‎ 121 pages
  • Dimensions‎:‎ 190.5 x 234.95 x 7.11mm ‎- 294.83g
  • Publication date‎:‎ 30 Apr 2014
  • Publisher‎:‎ Morgan & Claypool Publishers
  • Imprint‎:‎ Morgan and Claypool Life Sciences
  • Publication City/Country‎:‎ San Rafael‎,‎ CA‎,‎ United States

Learning from Demonstration ‎(‎LfD‎)‎ explores techniques for learning a task policy from examples provided by a human teacher‎.‎ The field of LfD has grown into an extensive body of literature over the past 30 years‎,‎ with a wide variety of approaches for encoding human demonstrations and modeling skills and tasks‎.‎ Additionally‎,‎ we have recently seen a focus on gathering data from non‎-expert human teachers ‎(‎i‎.‎e‎.‎‎,‎ domain experts but not robotics experts‎)‎‎.‎ In this book‎,‎ we provide an introduction to the field with a focus on the unique technical challenges associated with designing robots that learn from naive human teachers‎.‎ We begin‎,‎ in the introduction‎,‎ with a unification of the various terminology seen in the literature as well as an outline of the design choices one has in designing an LfD system‎.‎ Chapter 2 gives a brief survey of the psychology literature that provides insights from human social learning that are relevant to designing robotic social learners‎.‎ Chapter 3 walks through an LfD interaction‎,‎ surveying the design choices one makes and state of the art approaches in prior work‎.‎First‎,‎ is the choice of input‎,‎ how the human teacher interacts with the robot to provide demonstrations‎.‎ Next‎,‎ is the choice of modeling technique‎.‎ Currently‎,‎ there is a dichotomy in the field between approaches that model low‎-level motor skills and those that model high‎-level tasks composed of primitive actions‎.‎ We devote a chapter to each of these‎.‎ Chapter 7 is devoted to interactive and active learning approaches that allow the robot to refine an existing task model‎.‎ And finally‎,‎ Chapter 8 provides best practices for evaluation of LfD systems‎,‎ with a focus on how to approach experiments with human subjects in this domain‎.‎

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