—Multicast is an important communication paradigm, also a problem well known for its difficulty (NP-completeness) to achieve certain optimization goals, such as minimum network ...
We consider the problem of multi-task reinforcement learning where the learner is provided with a set of tasks, for which only a small number of samples can be generated for any g...
We present a system for regression using MLP neural networks with hyperbolic tangent functions in the input, hidden and output layer. The activation functions in the input and outp...
In this paper, we present a new simulation platform for complex, radio standard spanning mobile Ad Hoc networks. SimANet - Simulation Platform for Ambient Networks - allows the coe...
Aggregation of data values plays an important role on distributed computations, in particular over peer-to-peer and sensor networks, as it can provide a summary of some global sys...