A markov-decision-based price comparison problem for mobile aGent-based internet commerce system (MAGICS)

摘要

Mobile agents are well suited for facilitating the consumer buying process on the Internet, particularly for comparing prices. In this paper, we present a mobile agent-based e-commerce system, called MAGICS, that addresses some issues concerning price comparisons. After providing an overview of the MAGICS architecture, we use the Markov decision theory to formulate a price comparison problem. The objective of the problem is to obtain an optimal decision policy in order to buy a product at the lowest expected cost, including the traveling costs. The problem was solved using the backward induction algorithm. Some analytical results are presented and discussed.