Knowledge discovery for adaptive negotiation agents in e-marketplaces
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.
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|Item Type:||Journal Article|
|Keywords:||Knowledge discovery, Bayesian learning, Adaptive negotiation agents, e-marketplaces|
|Subjects:||Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Pattern Recognition and Data Mining (080109)|
|Divisions:||Past > QUT Faculties & Divisions > Faculty of Science and Technology
Past > Institutes > Institute for Creative Industries and Innovation
|Copyright Owner:||Copyright © 2008 Elsevier B.V. All rights reserved.|
|Deposited On:||04 Dec 2009 05:30|
|Last Modified:||29 Feb 2012 13:47|
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