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doi:10.22028/D291-25226
Titel: | The eager bidder problem : a fundamental problem of DAI and selected solutions |
VerfasserIn: | Schillo, Michael Fischer, Klaus Kray, Christian |
Sprache: | Englisch |
Erscheinungsjahr: | 2001 |
Quelle: | Kaiserslautern ; Saarbrücken : DFKI, 2001 |
Kontrollierte Schlagwörter: | Künstliche Intelligenz |
Freie Schlagwörter: | task assignment contract net protocol commitment coordination bidding agents |
DDC-Sachgruppe: | 004 Informatik |
Dokumenttyp: | Forschungsbericht (Report zu Forschungsprojekten) |
Abstract: | The contract net protocol [17] [18] is a widely used protocol in DAI, as it proved to be a flexible and low communication interaction protocol for task assignment. It is however not clear how agents participating in a contract net should allocate their resources, if a large number of contract nets is performed concurrently. If the agent allocates too many resources at an early stage, it may not get its bid accepted and therefore resources are not available for other tasks, if it allocates too late, it may have committed to do more tasks than its resources allow for. In this paper we present an ad hoc solution and two more complex strategies for solving this problem. Furthermore, we introduce a new method based on a statistic approach. We describe these mechanisms and how they deal with the concept of commitment on different levels. There is no optimal solution for every problem setting, but each has advantages and disadvantages. Our discussion concludes with criteria for the decision on which of these mechanisms is best to select for a given problem domain. |
Link zu diesem Datensatz: | urn:nbn:de:bsz:291-scidok-50434 hdl:20.500.11880/25282 http://dx.doi.org/10.22028/D291-25226 |
Schriftenreihe: | Research report / Deutsches Forschungszentrum für Künstliche Intelligenz [ISSN 0946-008x] |
Band: | 01-03 |
Datum des Eintrags: | 7-Feb-2013 |
Fakultät: | SE - Sonstige Einrichtungen |
Fachrichtung: | SE - DFKI Deutsches Forschungszentrum für Künstliche Intelligenz |
Sammlung: | SciDok - Der Wissenschaftsserver der Universität des Saarlandes |
Dateien zu diesem Datensatz:
Datei | Beschreibung | Größe | Format | |
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RR_01_03_.pdf | 6,75 MB | Adobe PDF | Öffnen/Anzeigen |
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