Intelligent Call Transfer Based on Reinforcement Learning
IJCNN '00 Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 6 - Volume 6
An Agent-Based Model for the Adaptation of Processing Efficiency for Prioritized Traffic
KES-AMSTA '09 Proceedings of the Third KES International Symposium on Agent and Multi-Agent Systems: Technologies and Applications
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This paper explores improvements that can be achieved by applying intelligent agent techniques to solve the problem of self-adaptive routing. A potential redundancy has been recognized in telecommunication network configuration, hidden in the routing method between the user access points and service providers. The main idea presented here is perpetual trans fer adaptation for all requests that are sent from a user to a service location over all the network elements. Self-adaptation is based on the continuous monitoring of the available communication channel capacity between the user and the service. The actions are based on perpetually seeking the optimal throughput via the nodes that maximize exploitation of the communication channel. From the user's point of view, accumulation and exploration of knowledge concerning throughput properties in the network can optimally utilize redundant capacities thus providing service more rapidly.