Reinforcement learning is an effective technique for learning action policies in discrete stochastic environments, but its efficiency can decay exponentially with the size of the ...
We show how the DOP model can be used for fast and robust processing of spoken input in a practical spoken dialogue system called OVIS. OVIS, Openbaar Vervoer Informatie Systeem (...
Word sense disambiguation for unrestricted text is one of the most difficult tasks in the fields of computational linguistics. The crux of the problem is to discover a model that ...
In this study, a learning device based on the PATtree data structures was developed. The original PAT-trees were enhanced with the deletion function to emulate human learning comp...
Much of the power of probabilistic methods in modelling language comes from their ability to compare several derivations for the same string in the language. An important starting...