Internet learning agents: a study of user performance with selected search engines

Searching for information on the Internet differs in significant ways. To adequately support retrieval tasks, search engines require an array of emerging technologies. As supporting tools, they are of great value to the user by providing relevant results specific to a given query. This study examined Internet agents from the perspective of fixed learning and evolutionary learning with selected search engines. Internet agents refer to the intelligent software residing in search engines to process and access information on behalf of the user. The goal of this research was to measure whether user performance varies as a result of retrieving information across selected agent types.