We present a framework of cognitive network management by means of an autonomic reconfiguration scheme. We propose a network
architecture that enables intelligent services to meet QoS requirements, by adding autonomous intelligence, based on reinforcement
learning, to the network management agents. The management system is shown to be better able to reconfigure its policy strategy
around areas of interest and adapt to changes. We present preliminary simulation results showing our autonomous reconfiguration
approach successfully improves the performance of the original AODV protocol in a heterogeneous network environment.
Keywords Cognitive networks - autonomic management - wireless mesh networks