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.
|Title of host publication||Web Engineering - 4th International Conference, ICWE 2004, Proceedings|
|Editors||Nora Koch, Martin Wirsing, Piero Fraternali|
|Number of pages||14|
|Publication status||Published - 2004|
|Event||4th International Conference on Web Engineering, ICWE 2004 - Munich, Germany|
Duration: 2004 Jul 26 → 2004 Jul 30
|Name||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|
|Other||4th International Conference on Web Engineering, ICWE 2004|
|Period||04/7/26 → 04/7/30|
Bibliographical notePublisher Copyright:
© Springer-Verlag Berlin Heidelberg 2004.
All Science Journal Classification (ASJC) codes
- Theoretical Computer Science
- Computer Science(all)