Quantifier Elimination for Statistical Problems

  • Dan Geiger ,
  • Chris Meek

Proceedings of Fifteenth Conference on Uncertainty in Artificial Intelligence, ® Stockholm, Sweden |

Published by Morgan Kaufmann

Recent improvements for Tarski’s procedure for quantifier elimination in the first order theory of real numbers makes it feasible to solve small instances of the following problems completely automatically: 1. listing all equality and inequality constraints implied by a graphical model with hidden variables. 2. Comparing graphical models with hidden variables (i.e., model equivalence, inclusion, and overlap). 3. Answering questions about the identification of a model or portion of a model, and about bounds on quantities derived from a model. 4. Determining whether an independence assertion is implied from a given set of independence assertions. We discuss the foundations of quantifier elimination and demonstrate its application to these problems.