Knowledge discovery for adaptive negotiation agents in e-marketplaces
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
Author(s)
Related Research Unit(s)
Detail(s)
Original language | English |
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Pages (from-to) | 310-323 |
Journal / Publication | Decision Support Systems |
Volume | 45 |
Issue number | 2 |
Publication status | Published - May 2008 |
Link(s)
Abstract
Intelligent software agents are promising in improving the effectiveness of e-marketplaces for e-commerce. Although a large amount of research has been conducted to develop negotiation protocols and mechanisms for e-marketplaces, existing negotiation mechanisms are weak in dealing with complex and dynamic negotiation spaces often found in e-commerce. This paper illustrates a novel knowledge discovery method and a probabilistic negotiation decision making mechanism to improve the performance of negotiation agents. Our preliminary experiments show that the probabilistic negotiation agents empowered by knowledge discovery mechanisms are more effective and efficient than the Pareto optimal negotiation agents in simulated e-marketplaces. © 2008 Elsevier B.V. All rights reserved.
Research Area(s)
- Adaptive negotiation agents, Bayesian learning, e-marketplaces, Knowledge discovery
Citation Format(s)
Knowledge discovery for adaptive negotiation agents in e-marketplaces. / Lau, Raymond Y.K.; Li, Yuefeng; Song, Dawei et al.
In: Decision Support Systems, Vol. 45, No. 2, 05.2008, p. 310-323.
In: Decision Support Systems, Vol. 45, No. 2, 05.2008, p. 310-323.
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review