A key issue in artificial intelligence lies in finding the amount of input detail needed to do successful learning. Too much detail causes overhead and makes learning prone to ove...
Machine learning typically involves discovering regularities in a training set, then applying these learned regularities to classify objects in a test set. In this paper we presen...
We apply CMA-ES, an evolution strategy with covariance matrix adaptation, and TDL (Temporal Difference Learning) to reinforcement learning tasks. In both cases these algorithms se...
It is widely recognized that today's Internet traffic is mostly carried by a relatively small number of elephant flows while mice flows constitute up to 80% of all active flow...
The point algebra is a fundamental formal calculus for spatial and temporal reasoning. We present a new generalization that meets all requirements to describe dependencies on netw...