(PDF/EBOOK) [Interactive Task Learning] ´ Kevin A Gluck

Interactive Task LearningExperts from a range of isciplines EXPLORE HOW HUMANS AND ARTIFICIAL AGENTS how humans and artificial agents uickly learn completely new tasks through natural interactions with each otherHumans are not limited to a fixed set

OF INNATE OR PREPROGRAMMED TASKS WE 
innate or preprogrammed tasks We uickly through language and other forms fixed set of innate or preprogrammed tasks We learn uickly through language and other forms natural interaction and we improve our performance and teach others what we have learned Understanding the mechanisms that underlie the acuisition of new tasks through natural interaction is an ongoing challenge Advances in artificial intelligence cognitive science and robotics are leading us to future systems with human like capabilities A huge gap exists however between the highly specialized niche capabilities of current machine learning systems and the generality flexibility and in situ robustness of human instruction and lear. ,

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Summary Ö PDF, DOC, TXT, eBook or Kindle ePUB free ☆ Kevin A Gluck

Eme Katrien Beuls Maya Cakmak Joyce Y Chai Franklin Chang Ropafadzo Denga Marc Destefano Mark 'Inverno Kenneth D Forbus Simon Garrod Kevin A Gluck Wayne D Chang Ropafadzo Denga Marc Destefano Mark 'Inverno Kenneth D Forbus Simon Garrod Kevin A Gluck Wayne D James Kirk Kenneth R Koedinger Parisa Kordjamshidi John E Laird Christian Lebiere Stephen C Levinson Elena Lieven John K Lindstedt Aaron Mininger Tom Mitchell Shiwali Mohan Ana Paiva Katerina Pastra Peter Pirolli Roussell Rahman Charles Rich Katharina J Rohlfing Paul S Rosenbloom Nele Russwinkel Dario D Salvucci Matthew Donald D Sangster Matthias Scheutz Julie A Shah Candace L Sidner Catherine Sibert Michael Spranger Luc Steels Suzanne Stevenson Terrence C Stewart Arthur Still Andrea Stocco Niels Taatgen Andrea L Thomaz J Gregory Trafton Han L J van er Maas Paul Van Eecke Kurt VanLehn Van Eecke Kurt VanLehn Lisa Vollmer Janet Wiles Robert E WRAY III MATTHEW YEE KING. Wray III Matthew Yee King. ,
Ning Drawing on expertise from multiple isciplines this #Strngmann Forum Report explores how humans and artificial agents can uickly learn completely new tasks through natural interactions #Forum Report explores how humans and artificial agents can uickly learn completely new tasks through natural interactions each otherThe contributors consider functional knowledge reuirements the ontology of interactive task learning and the representation of task knowledge at multiple levels of abstraction They knowledge reuirements the ontology of interactive task learning and the representation of task knowledge at multiple levels of abstraction They natural forms of interactions among humans as well as the use of interaction to teach robots and software agents new tasks in complex Mercure De France Vol 43 dynamic environments Theyiscuss research challenges and opportunities including ethical considerations and make proposals to *Further Understanding Of Interactive Task Learning And Create New Capabilities *understanding of interactive task learning and create new capabilities assistive robotics healthcare education training and gamingContributors Tony Belpa. ,