Intelligent foraging, gathering and matching (I-FGM) has been shown to be an effective tool for intelligence analysts who have to deal with large and dynamic search spaces. I-FGM introduced a unique resource allocation strategy based on a partial information processing paradigm which, along with a modular system architecture, makes it a truly novel and comprehensive solution to information retrieval in such search spaces. This paper provides further validation of its performance by studying its behavior while working with highly dynamic databases. Results from earlier experiments were analyzed and important changes have been made in the system parameters to deal with dynamism in the search space. These changes also help in our goal of providing relevant search results quickly and with minimum wastage of computational resources. Experiments have been conducted on I-FGM in a realistic and dynamic simulation environment, and its results are compared with two other control systems. I-FGM clearly outperforms the control systems.