An efficient automated negotiation system using multi-attributes in the online environment

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)


In this paper we propose an efficient negotiation agent system that guarantees the reciprocity of the attendants in a bilateral negotiation on the ecommerce. The proposed negotiation agent system exploits incremental learning based on artificial neural networks to generate counter-offers and is trained by the previous offers that have been rejected by the other party. During a negotiation, the software agents on behalf of the buyer and the seller negotiate each other by considering the multi-attributes of a product. The experimental results show that the proposed negotiation system achieves better agreements than other negotiation agent systems that can be operable under the realistic and practical environment. Furthermore, the proposed system carries out negotiations about twenty times faster than other negotiation systems on the average.

Original languageEnglish
Title of host publicationWeb Engineering - 4th International Conference, ICWE 2004, Proceedings
EditorsNora Koch, Martin Wirsing, Piero Fraternali
PublisherSpringer Verlag
Number of pages14
ISBN (Print)3540225110
Publication statusPublished - 2004
Event4th International Conference on Web Engineering, ICWE 2004 - Munich, Germany
Duration: 2004 Jul 262004 Jul 30

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other4th International Conference on Web Engineering, ICWE 2004

Bibliographical note

Publisher Copyright:
© Springer-Verlag Berlin Heidelberg 2004.

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • General Computer Science


Dive into the research topics of 'An efficient automated negotiation system using multi-attributes in the online environment'. Together they form a unique fingerprint.

Cite this