Abstract
A Computer Network which automatically configures itself and adopts the services which fulfil user requirements according to their needs is called autonomic network. Autonomic network self manages the services for heterogeneous devices and modify polices for users to satisfy them from network services. In ENhanced Autonomic network Management Architecture (ENAMA), we propose two blocks of processing which control the operations of management as well as for learning from environment and take decisions for network related issues. QoE will be used for collecting data for learning from external environment and store in Long Term Memory (LTM) block for future analysis and decisions. The proposed ENAMA is the fast learning autonomic network management architecture; it will take most accurate decisions to handle the critical situations.