We present a new analytical approach for the performance evaluation of asynchronous wormhole routing in k-ary n-cubes. Through the analysis of network flows, our methodology furni...
Bruno Ciciani, Claudio Paolucci, Michele Colajanni
In this paper we consider the problem of policy evaluation in reinforcement learning, i.e., learning the value function of a fixed policy, using the least-squares temporal-differe...
Alessandro Lazaric, Mohammad Ghavamzadeh, Ré...
BOINC is a platform for volunteer computing. The server component of BOINC embodies a number of scheduling policies and parameters that have a large impact on the projects through...
Trilce Estrada, Michela Taufer, Kevin Reed, David ...
We identify two fundamental points of utilizing CBR for an adaptive agent that tries to learn on the basis of trial and error without a model of its environment. The first link co...
We focus on control systems in which sensors send data to actuators via a bus shared with other applications. An approach is proposed for specifying and implementing dynamic schedu...
Gera Weiss, Sebastian Fischmeister, Madhukar Anand...