— This paper presents a method to autonomously extract object features that describe their dynamics from active sensing experiences. The model is composed of a dynamics learning ...
An important theoretical tool in machine learning is the bias/variance decomposition of the generalization error. It was introduced for the mean square error in [3]. The bias/vari...
Despite the recognition of cellular automata (CA) as a exible and powerful tool for urban growth simulation, the calibration of CA had been largely heuristic until recent eVorts to...
—This paper describes a multi-agent based simulation (MABS) framework to construct an artificial electric power market populated with learning agents. The artificial market, na...
Artificial Neural Networks (ANN) are an emerging technology, yet, in continuous dynamic behavior, much work has been done to attempt to generate a formal method to design a contro...