BargainBot parallel, multiagent architecture Findings and Issues Purchasing books with the aid of Bargainbot has time and money saving advantages. Performing similar tasks would entail tracking down and searching multiple bookstores on the Internet, a time consuming process. Bargainbot does not suffer the inefficiencies of recursive retrieval associated with conventional robots. Bargainbot knows exactly where to locate its information and does not produce recursive hits on a server or excessive stress on the network. The development and use of Bargainbot has highlighted numerous issues that need to be addressed if automated browsing, and specifically automated querying of site databases, is to remain a useful complement to manual browsing on the network.
Many online stores provide little support for effective information querying of their databases.
For example, many bookstores that Bargainbot searches, have a Web forms front-end to their database that limits querying to either title or author, but not both simultaneously. This requires Bargainbot to perform an extra level of filtering to remove unwanted authors from a returned list of book titles. The format of data returned from bookstore sites also varies. Bargainbot must apply different filtering mechanisms to different sites in order to return combined results in a homogeneous manner. Furthermore, changes to the format of bookstore responses requires programmer intervention.