umu.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
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, Published 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
Robotics
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:umu:diva-52240OAI: oai:DiVA.org:umu-52240DiVA: diva2:501529
Conference
Umeå's 15th Student Conference in Computing Science (USCCS 2012), 18th of January 2012, Umeå
Projects
INTRO
Funder
EU, FP7, Seventh Framework Programme, 238486
Available from: 2012-02-20 Created: 2012-02-14 Last updated: 2012-02-20Bibliographically approved

Open Access in DiVA

fulltext(340 kB)164 downloads
File information
File name FULLTEXT02.pdfFile size 340 kBChecksum SHA-512
7e7e4e2b9d16c369478bfec2189363164178a6bcdbc16303c7f47bf714eebbc56f37e43c733b6920e71695d2e117c4a3d9eb2b16521f1ec53859ad08d8906f96
Type fulltextMimetype application/pdf

Authority records BETA

Fonooni, Benjamin

Search in DiVA

By author/editor
Fonooni, Benjamin
By organisation
Department of Computing Science
Robotics

Search outside of DiVA

GoogleGoogle Scholar
Total: 164 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

urn-nbn

Altmetric score

urn-nbn
Total: 121 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf