We propose a new approach to reinforcement learning which combines least squares function approximation with policy iteration. Our method is model-free and completely off policy. ...
In many applications extraction of source signals of interest from observed signals maybe is a more feasible approach than simultaneous separation of all the source signals, since...
—Knowledge of a network’s topology and internal characteristics such as delay times or losses is crucial to maintain seamless operation of network services. Network tomography ...
A Bayesian network model is a popular technique for data mining due to its intuitive interpretation. This paper presents a semantic genetic algorithm (SGA) to learn a complete qual...
The paper presents an extended hand-eye calibration approach that, in contrast to the standard method, does not require a calibration pattern for determining camera position and or...