Design-time decisions can often only cover certain scenarios and fail in efficiency when hard-to-predict system scenarios occur. This drives the development of run-time adaptive systems. To the best of our knowledge, we are presenting the first scheme for a run-time application mapping in a distributed manner using agents targeting for adaptive NoC-based heterogeneous multi-processor systems. Our approach reduces the overall traffic produced to collect the current state of the system (monitoring-traffic), needed for runtime mapping, compared to a centralized mapping scheme. In our experiment, we obtain 10.7 times lower monitoring traffic compared to the centralized mapping scheme proposed in [8] for a 64 x 64 NoC. Our proposed scheme also requires less execution cycles compared to a non-clustered centralized approach. We achieve on an average 7.1 times lower computational effort for the mapping algorithm compared to the simple nearest-neighbor (NN) heuristics proposed in [6] in a 64 x 32 NoC. We demonstrate the advantage of our scheme by means of a robot application and a set of multimedia applications and compare it to the state-of-the-art run-time mapping schemes proposed in [6, 8, 19].