In this paper, we propose a stochastic version of a general purpose functional programming language as a method of modeling stochastic processes. The language contains random choi...
Bayesian networks provide a modeling language and associated inference algorithm for stochastic domains. They have been successfully applied in a variety of medium-scale applicati...
We have implemented an incremental lexical acquisition mechanism that learns the meanings of previously unknown words from the context in which they appear, as a part of the proce...
Mostexisting decision-theoretic planners represent uncertainty about the state of the world with a precisely specified probability distribution over world states. This representat...
Both full-text information retrieval and large scale parsing require text preprocessing to identify strong lexical associations in textual databases. In order to associate linguis...