Abstract - The rapid expansion of digital content on the World Wide Web has made efficient information retrieval an increasingly complex challenge. To assist users in navigating this vast information landscape, several retrieval mechanisms have been developed. Among these, two broad strategies are commonly employed: structured index-based search and autonomous agent-driven search. This work presents an intelligent search agent that leverages a Genetic Algorithm (GA) to perform global web searches. The agent is implemented using the Java programming language and operates by evaluating multiple candidate documents to identify the most relevant result for a given input. The proposed system is built on the Java platform and integrates the Merriam-Webster lexical database to expand query terms with their semantic equivalents. Query words are tokenized, synonym tables are constructed, and varied term combinations are assembled and dispatched to a search engine parser. The returned web pages represent the most semantically aligned results for the original query. Key Words: Genetic Algorithm, web page retrival, searching.