Four search... Search engines are usually made popular through social networks, but users are skeptical and rely on trust and competency of results before adopting a preferred engine. Two agent types were tested, fixed agents that learn statically from the user queries and evolutionary agents that learn dynamically from user communities with similar inquiries. The study presented here offers a balanced coverage of how users perform with Internet agents. The effective use of any intelligent software requires evaluation practices to measure how the user performs in relation to the technology. While search engines are built on AI, they are tightly anchored to the principles of HCI and human-agent interaction. Synthesizing on user performance, studies show that several attributes in the theory of action describe the sequence of steps behind a person interfacing with computers. Internet agents are at the heart of web search engines and support the user with flexibility on information search.