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Sequential Learning From Demonstration Based On Semantic Networks
Umeå University, Faculty of Science and Technology, Department of Computing Science. (Robotics)
2012 (English)In: Proceedings of Umeå's 15th Student Conference in Computing Science (USCCS 2012) / [ed] Suna Bensch, Frank Drewes, Håkan Gulliksson and Thomas Mejtoft, Umeå: Umeå University , 2012, 39-47 p.Conference paper (Refereed)
Abstract [en]

Most of the humans day to day tasks include sequences ofactions that lead to a desired goal. In domains which humans are replacedby robots, the ability of learning new skills easy and fast plays animportant role. The aim of this research paper is to incorporate sequentiallearning into Learning from Demonstration (LfD) in an architecturewhich mainly focuses on high-level representation of behaviors. The primarygoal of the research is to investigate the possibility of utilizingSemantic Networks in order to enable the robot to learn new skills insequences.

Place, publisher, year, edition, pages
Umeå: Umeå University , 2012. 39-47 p.
Keyword [en]
Sequential Learning, Learning from Demonstration, Semantic Networks, High-Level Behaviors, Robot Learning
National Category
Research subject
Computer Science
URN: urn:nbn:se:umu:diva-52240OAI: diva2:501529
Umeå's 15th Student Conference in Computing Science (USCCS 2012), 18th of January 2012, Umeå
EU, FP7, Seventh Framework Programme, 238486
Available from: 2012-02-20 Created: 2012-02-14 Last updated: 2012-02-20Bibliographically approved

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Fonooni, Benjamin
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