Please use this identifier to cite or link to this item: doi:10.22028/D291-24955
Title: COSMA - multi-participant NL interaction for appointment scheduling
Author(s): Busemann, Stephan
Oepen, Stephan
Hinkelman, Elizabeth A.
Neumann, Günter
Uszkoreit, Hans
Language: English
Year of Publication: 1994
OPUS Source: Kaiserslautern ; Saarbrücken : DFKI, 1994
SWD key words: Künstliche Intelligenz
DDC notations: 004 Computer science, internet
Publikation type: Report
Abstract: We discuss the use of NL systems in the domain of appointment scheduling. Appointment scheduling is a problem faced daily by many people and organizations, and typically solved using communication in natural language. In general, cooperative interaction between several participants is required whose calendar data are distributed rather than centralized. In this distributed multi-agent environment, the use of NL systems makes it possible for machines and humans to cooperate in solving scheduling problems. We describe the COSMA (Cooperative Schedule Managament Agent) system, a secretarial assistant for appointment scheduling. A central part of COSMA is the reusable NL core system DISCO, which serves, in this application, as an NL interface between an appointment planning system and the human user. COSMA is fully implemented in Common Lisp and runs on Unix Workstations. Our experience with COSMA shows that it is a plausible and useful application for NL systems. However, the appointment planner was not designed for NL communication and thus makes strong assumptions about sequencing of domain actions and about the error-freeness of the communication. We suggest that further improvements of the overall COSMA functionality, especially with regard to flexibility and robustness, be based on a modified architecture.
Link to this record: urn:nbn:de:bsz:291-scidok-37337
Series name: Research report / Deutsches Forschungszentrum für Künstliche Intelligenz [ISSN 0946-008x]
Series volume: 94-34
Date of registration: 30-Jun-2011
Faculty: SE - Sonstige Einrichtungen
Department: SE - DFKI Deutsches Forschungszentrum für Künstliche Intelligenz
Collections:SciDok - Der Wissenschaftsserver der Universität des Saarlandes

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