Resource deployment is an effective means to improve search performance and can also be used to enhance the availability of resource replicas in unstructured P2P networks. Most of the current studies focus on the quantitative analysis of various types of resource replicas and distributed deployment strategies. During the resource deployment process each node selects resource replica exclusively for deployment; however, the process lacks a consideration for deployment behavior interactions among participating nodes. In a P2P network, each node keeps in touch with several other neighbors and are aware of local information, so each node can be assumed to be bounded rational. This paper designs the performance-related payoff function through analyzing the relation between search performance and resource deployment behaviors of nodes, and then models the resource deployment as an evolutionary game. In terms of the description of game evolution, the study can effectively analyze the interactions among nodes and the expected search performance. The simulation results indicate that the proposed resource deployment evolutionary model achieves higher success rate and approximate optimal average hop counts while maintaining a relatively low redundancy.