We present a probabilistic formulation of UCS (a sUpervised Classifier System). UCS is shown to be a special case of mixture of experts where the experts are learned independentl...
Narayanan Unny Edakunni, Tim Kovacs, Gavin Brown, ...
We recently proposed a new approach to parallelization, by decomposing the time domain, instead of the conventional space domain. This improves latency tolerance, and we demonstrat...
We describe our preliminary work in modeling conversation specifications and policies as positive/negative permissions and obligations. Our model is generic as it is independent o...
Abstract—Learning dynamical systems is one of the important problems in many fields. In this paper, we present an algorithm for learning non-linear dynamical systems which works...
Conditional real-time task models, which are generalizations of periodic, sporadic, and multi-frame tasks, represent real world applications more accurately. These models can be c...
Madhukar Anand, Arvind Easwaran, Sebastian Fischme...