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

Sanghyun Park; Sung Bong Yang

doi:10.1007/978-3-540-27834-4_66

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

Sanghyun Park, Sung Bong Yang

Department of Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

2 Citations (Scopus)

Abstract

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 language	English
Title of host publication	Web Engineering - 4th International Conference, ICWE 2004, Proceedings
Editors	Nora Koch, Martin Wirsing, Piero Fraternali
Publisher	Springer Verlag
Pages	544-557
Number of pages	14
ISBN (Print)	3540225110
DOIs	https://doi.org/10.1007/978-3-540-27834-4_66
Publication status	Published - 2004
Event	4th International Conference on Web Engineering, ICWE 2004 - Munich, Germany Duration: 2004 Jul 26 → 2004 Jul 30

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	3140
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Other

Other	4th International Conference on Web Engineering, ICWE 2004
Country	Germany
City	Munich
Period	04/7/26 → 04/7/30

Bibliographical note

Publisher Copyright:
© Springer-Verlag Berlin Heidelberg 2004.

All Science Journal Classification (ASJC) codes

Theoretical Computer Science
Computer Science(all)

Access to Document

10.1007/978-3-540-27834-4_66

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Park, S., & Yang, S. B. (2004). An efficient automated negotiation system using multi-attributes in the online environment. In N. Koch, M. Wirsing, & P. Fraternali (Eds.), Web Engineering - 4th International Conference, ICWE 2004, Proceedings (pp. 544-557). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3140). Springer Verlag. https://doi.org/10.1007/978-3-540-27834-4_66

Park, Sanghyun ; Yang, Sung Bong. / An efficient automated negotiation system using multi-attributes in the online environment. Web Engineering - 4th International Conference, ICWE 2004, Proceedings. editor / Nora Koch ; Martin Wirsing ; Piero Fraternali. Springer Verlag, 2004. pp. 544-557 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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abstract = "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.",

author = "Sanghyun Park and Yang, {Sung Bong}",

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Park, S & Yang, SB 2004, An efficient automated negotiation system using multi-attributes in the online environment. in N Koch, M Wirsing & P Fraternali (eds), Web Engineering - 4th International Conference, ICWE 2004, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 3140, Springer Verlag, pp. 544-557, 4th International Conference on Web Engineering, ICWE 2004, Munich, Germany, 04/7/26. https://doi.org/10.1007/978-3-540-27834-4_66

An efficient automated negotiation system using multi-attributes in the online environment. / Park, Sanghyun ; Yang, Sung Bong.

Web Engineering - 4th International Conference, ICWE 2004, Proceedings. ed. / Nora Koch; Martin Wirsing; Piero Fraternali. Springer Verlag, 2004. p. 544-557 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3140).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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N2 - 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.

AB - 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.

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Park S , Yang SB. An efficient automated negotiation system using multi-attributes in the online environment. In Koch N, Wirsing M, Fraternali P, editors, Web Engineering - 4th International Conference, ICWE 2004, Proceedings. Springer Verlag. 2004. p. 544-557. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-540-27834-4_66

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

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