For many real-time applications running over packet-switched networks, it is important to maintain delivered data quality using a limited amount of network resources. It is therefore natural to employ cost functions that allow online trade-off between the experienced application quality and the resource usage. However, minimizing such cost functions requires perfect knowledge of the network state at the transmission side, while, in general, such information is only partially available. In this paper, we introduce a new adaptive error correction algorithm that optimizes the amount of redundancy based on the available information from the application and the network. An extremum-seeking control algorithm is employed to deal with the high level of uncertainty in the network models. The validity of our approach is illustrated in simulations with varying network loads and loss correlation.