In ongoing research, a collaborative peer network application is being proposed to address the scalability limitations of centralized search engines. Here we introduce a local adaptive routing algorithm used to dynamically change the topology of the peer network based on a simple learning scheme driven by query response interactions among neighbors. We test the algorithm via simulations with 70 model users based on actual Web crawls. We find that the network topology rapidly converges from a random network to a small world network, with emerging clusters that match the user communities with shared interests. Categories and Subject Descriptors: C.2.4 [Computer-Communication Networks]: Distributed Systems; H.3.3 [Information Storage and Retrieval]: Information Search and Retrieval General Terms: Algorithms, Measurement