In robotic navigation, path planning is aimed at getting the optimum collision-free
path between a starting and target locations. The optimality criterion depends on
the surround...
Kernel k-means and spectral clustering have both been used to identify clusters that are non-linearly separable in input space. Despite significant research, these methods have re...
Commitment protocols formalize interactions among autonomous, heterogeneous agents, leaving the agents’ local policies unspecified. This paper studies the problem of agents ena...
Abstract. Tuning hyper-parameters is a necessary step to improve learning algorithm performances. For Support Vector Machine classifiers, adjusting kernel parameters increases dra...
Inspired by psychophysical studies of the human cognitive abilities we propose a novel aspect and a method for performance evaluation of contour based shape recognition algorithms ...