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Zitierlink URN
https://nbn-resolving.de/urn:nbn:de:gbv:46-00102274-16

Relevanzbasierte Informationsbeschaffung für die informierte Entscheidungsfindung intelligenter Agenten

Veröffentlichungsdatum
2011-09-23
Autoren
Gehrke, Jan Dirk  
Betreuer
Herzog, Otthein  
Gutachter
Lamersdorf, Winfried  
Zusammenfassung
This dissertation introduces relevance-based information acquisition for intelligent software agents based on Howard s information value theory and decision networks. Active information acquisition is crucial in domains with partial observability in order to establish situation awareness of autonomous systems for deliberate decisions. The new semi-myopic approach addresses the complexity challenge of decision-theoretic relevance computation by reducing the set of variables to be evaluated in the first place. Links in a decision network encode stochastic dependencies of variables. Through utility dependency analysis using Pearl s d-separation criterion, the set of relevant variables can be efficiently reduced to a proven minimum without actually computing information value. In addition to an implementation with detailed runtime performance analysis, the applicability of the approach is shown in the domain of intelligent logistics control.
Schlagwörter
Intelligent Agents

; 

Information Value

; 

Information Acquisition

; 

Decision Networks

; 

Situation Awareness

; 

Autonomous Logistics
Institution
Universität Bremen  
Fachbereich
Fachbereich 03: Mathematik/Informatik (FB 03)  
Dokumenttyp
Dissertation
Zweitveröffentlichung
Nein
Sprache
Deutsch
Dateien
Lade...
Vorschaubild
Name

00102274-1.pdf

Size

4.52 MB

Format

Adobe PDF

Checksum

(MD5):a207774c403a6283d88447aef57543f1

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