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Evaluation metrics for an experience-based mobile artificial cognitive system
University of Hamburg, Germany.
Örebro University, School of Science and Technology, Örebro University, Sweden. (AASS)ORCID iD: 0000-0001-8229-1363
Örebro University, School of Science and Technology, Örebro University, Sweden. (AASS)ORCID iD: 0000-0002-9652-7864
University of Hamburg, Germany.
2014 (English)In: 11th World Congress on Intelligent Control and Automation (WCICA2014), Springer Berlin/Heidelberg, 2014, 2225-2232 p.Conference paper, (Refereed)
Abstract [en]

In this paper, an FIM (Fitness to Ideal Model)and a DLen (Description Length) based evaluation approachhas been developed to measure the benefit of learning from experienceto improve the robustness of the robot’s behavior. Theexperience based mobile artificial cognitive system architectureis briefly described and adopted by a PR2 service robot withinthe EU-FP7 funded project RACE. The robot conducts typicaltasks of a waiter. Temporal and lasting obstacles and standardtable items, as shown in the demonstrations of “Deal-withobstacles”and “Clear-table-intelligently”, are being adoptedin this work to test the proposed evaluation metrics, validateit on a real PR2 robot system and present the evaluationresults. The relationship between the FIM and DLen has beenvalidated. This work proposes an effective approach to evaluatea cognitive service robot system which enhances its performanceby learning.

Place, publisher, year, edition, pages
Springer Berlin/Heidelberg, 2014. 2225-2232 p.
National Category
Computer Science
Research subject
Computer Science
Identifiers
URN: urn:nbn:se:oru:diva-41662ISBN: 978-3-642-28961-3 (print)OAI: oai:DiVA.org:oru-41662DiVA: diva2:780865
Conference
11th World Congress on Intelligent Control and Automation (WCICA2014). June 29-July 4, 2014. Shenyang, China.
Projects
Robustness by Autonomous Competence Enhancement (RACE)
Funder
EU, FP7, Seventh Framework Programme, 287752
Available from: 2015-01-15 Created: 2015-01-15 Last updated: 2017-03-16Bibliographically approved

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Saffiotti, AlessandroPecora, Federico
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School of Science and Technology, Örebro University, Sweden
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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • 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