Modeling e-procurement as co-adaptive matchmaking with mutual relevance feedback

Reiko Hishiyama*, Toru Ishida


研究成果: Conference article査読

5 被引用数 (Scopus)


This paper proposes a new e-procurement model for a large number of buyers and sellers interacting via the Internet. The goal of e-procurement is to create a satisfactory match between buyers' demand and sellers' supply. From our real-world experience, we view e-procurement as a process of negotiation to increase the matching quality of two corresponding specifications: one for buyers' demand and another for sellers' supply. To model scalable e-procurement, we propose a co-adaptive matchmaking mechanism using mutual relevance feedback. In order to understand the nature of the mechanism, we have developed two types of software agents, called e-buyers and e-sellers, to simulate human buyers and sellers. Multiagent simulation results show that the matching quality is incrementally improved if agents adaptively change their specifications. A realistic example is also provided to discuss how to extend our simulation to real-world e-procurement infrastructure.

ジャーナルLecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)
出版ステータスPublished - 2005
イベント7th Pacific Rim International Workshop on Multi-Agents, PRIMA 2004 - Auckland, New Zealand
継続期間: 2004 8月 82004 8月 13

ASJC Scopus subject areas

  • 理論的コンピュータサイエンス
  • コンピュータ サイエンス(全般)


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