We use simulated soccer to study multi-agent learning. Each team member tries to learn from the corresponding human player in a real game. Following a uniied approach, strategic and tactical behavior is learned synergistically by training a feed-forward neural network (ANN) with a mod-iied back-propagation algorithm. It aims at decreasing the learning time and avoiding the local maximums. We tr...

This paper explores the potential of extreme learning machine based supervised classification algorithm for land cover classification. In comparison to a backpropagation neural network, which requires setting of several user-defined parameters and may produce local minima, extreme learning machine require setting of one parameter and produce a unique solution. ETM+ multispectral data set (Engla...