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Findings and Issues
Figure 3. BargainBot parallel, multiagent architecture
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.
Eichmann [Eichmann 1994] examines the ethics of Web-based agents. 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. Further filtering is required to remove
redundant markup (HTML) from returned responses. 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. The use of machine learning techniques to sense and adapt to such changes will be
crucial to the success of similar agents in future filtering tasks.
Other problems associated with automated browsing of the Web include the presence of client-side state
mechanisms to store state information on the client side. State information, whilst useful for manual browsing
of interconnected pages, is often meaningless in the context of automated browsing, resulting in agents having
interface problems with site databases that expect such information. Certain sites also make use of session
keys, which time-out after short time intervals, requiring their continual renewal.
The above problems could be overcome by the introduction of a suitable merchandise request protocol. Other
possible querying mechanisms include Z39.50 [Kunze] or an inter-operable agent model [Genesereth et al.
1994]. Technical cooperation amongst site administrators and agent maintainers is also needed for the effective
use of agent technology in electronic commerce. For example, certain sites blocked the BargainFinder agent
[URL 2] from searching their databases.
The use of Java [Gosling & McGilton] as an agent implementation language is being looked at by many
researchers [URL 3] [URL 4]. Client side execution of agents have numerous advantages. For example, clientside
execution of network operations overcomes traffic routing that server based filtering mechanisms produce,
hence placing less stress on the network. Figure 4 illustrates Bargainbot interrogating remote bookstore
databases, filtering its findings, and returning the information to the user's browser. Figure 5 shows the
network operations of a client side agent, such as one written as a Java applet. Note there is only one set of
network operations required.