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Emotion-Driven Learning Agent for Setting Rich Presence in Mobile Telephony
KTH, School of Information and Communication Technology (ICT).
2008 (English)In: 2008 11TH INTERNATIONAL CONFERENCE ON COMPUTER AND INFORMATION TECHNOLOGY: ICCIT 2008, VOLS 1 AND 2, NEW YORK: IEEE , 2008, p. 552-557Conference paper, Published paper (Refereed)
Abstract [en]

Presence or personal status information is going to be an integral part of human life in the near future. With the possibility of personalizing user preferences in a fine grained way, mobile presence will appeal to most users. Among all the advantages, one of the most annoying problems is to set the presence status manually each time. This paper discusses the development of an intelligent agent based presence client that will learn and make decisions on behalf of the user about his or her presence status. The decision is emotion driven and the learning depends on real world experience. The proposed system utilizes a neural network (NN) based emotion-driven agent to learn user preferences. As a NN learning algorithm, two approaches based on Differential Evolution and Reinforcement have been proposed, of which either one can be used. Rich presence status is set using a scripting language named Call Processing Language; and SIP is used for publishing the presence to others.

Place, publisher, year, edition, pages
NEW YORK: IEEE , 2008. p. 552-557
Keyword [en]
Presence, neural network, ANN, CPL, context aware, learning agent, SIP, DE, reinforcement
National Category
Computer and Information Sciences
Identifiers
URN: urn:nbn:se:kth:diva-30797DOI: 10.1109/ICCITECHN.2008.4803023ISI: 000267674500094Scopus ID: 2-s2.0-66149168817ISBN: 978-1-4244-2135-0 (print)OAI: oai:DiVA.org:kth-30797DiVA, id: diva2:403467
Conference
11th International Conference on Computer and Information Technology Khulna, BANGLADESH, DEC 24-27, 2008
Note
QC 20110314Available from: 2011-03-14 Created: 2011-03-04 Last updated: 2018-01-12Bibliographically approved

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CiteExportLink to record
Permanent link

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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