In order to construct and deploy massively multiagent systems, we must address one of the fundamental issues of distributed systems, the possibility of partial failures. In this paper, we discuss the issues and propose an approach for fault-tolerance of massively multiagent systems. The starting idea is the application of replication strategies to agents. As criticality of agents may evolve during the course of computation and problem solving, and as resources are bounded, we need to dynamically and automatically adapt the number of replicas of agents, in order to maximize their reliability and availability. We will describe our approach and related mechanisms for evaluating the criticality of a given agent and how to parameterize it (e.g., number of replicas). We also will report on experiments conducted with our prototype architecture (named DarX).