The present study aims at insights into the nature of incremental learning in the context of Gold’s model of identification in the limit. With a focus on natural requirements s...
Recent research in machine learning has focused on supervised induction for simple classi cation and reinforcement learning for simple reactive behaviors. In the process, the eld ...
The main claim of this paper is that machine learning can help integrate the construction of ontologies and extraction grammars and lead us closer to the Semantic Web vision. The p...
Parallel discrete event simulation (PDES) techniques have not yet made a substantial impact on the network simulation community because of the need to recast the simulation models...
We present worst case bounds for the learning rate of a known prediction method that is based on hierarchical applications of binary context tree weighting (CTW) predictors. A heu...