We address the problem of searching for microblogs referring to events, which are difficult to find because microblogs may refer to events without using event's contents and a searcher may not use suitable queries for a search engine. We therefore propose a dynamic search process based on MDP that takes query strategies optimized for the current search state. As key components of the dynamic search process, we propose an RNN-based model for predicting long-term returns of a search process, and a DNN-based model that tries to match between the representations of microblogs and those of events for identifying relevant microblogs. Experimental results suggest that the dynamic search process could effectively search for microblogs, especially for implicitly referred events. Moreover, we show high applicability of our proposed approach to unseen events for which any relevant microblogs were not available in the training phase.