A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2018; you can also visit the original URL.
The file type is
The advent of e-commerce has brought about a radical change in the process of auctions that can be achieved by using agents. One of the important capabilities of agent is learning from the environment. In this paper, the authors are proposing case based learning for agents in online e-auctions. Case-based reasoning (CBR) is a problem solving paradigm based on the principle that similar problems have similar solutions has inherent learning capability. In auctions, CBR has been proposed to storefatcat:ftktf2ampjeqtjn5cakmd2uemq