This paper describes a novel network model, which is able to control its growth on the basis of the approximation requests. Two classes of self-tuning neural models are considered...
A. Carlevarino, R. Martinotti, Giorgio Metta, Giul...
—Increasing demand to transmit real-time data over packet-switched networks calls for quality-of-service support from the underlying network. Deadline-based networks were develop...
In this paper we present neuro-evolution of neural network controllers for mobile agents in a simulated environment. The controller is obtained through evolution of hypercube encod...
Congestion control algorithms are traditionally evaluated in contrast to ideal capacity allocations that specify instantaneous efficient fair rates for application sessions but i...
We describe how the new Datagram Congestion Control Protocol (DCCP) can be used as a bearer for the Real-time Transport Protocol (RTP) to provide a congestion controlled basis for...