We develop a hierarchical approach to planning for partially observable Markov decision processes (POMDPs) in which a policy is represented as a hierarchical finite-state control...
Thewidespreaduse of influence diagramsto represent andsolve Bayesiandecision problemsis still limited by the inflexibility andrather restrictive semanticsof influence diagrams. In...
This paper proposes a new novel method for the online construction of a Hierarchical Fuzzy Rule Based System (FRBS) to accurately model a function while retaining a level of human...
We describe a novel technique and implemented system for constructing a subcategorization dictionary from textual corpora. Each dictionary entry encodes the relative frequency of ...
We develop an approach for a sparse representation for Gaussian Process (GP) models in order to overcome the limitations of GPs caused by large data sets. The method is based on a...