A Forgetting-based Approach to Merging Knowledge Bases
  This paper presents a novel approach based on variable forgetting, which is a
useful tool in resolving contradictory by filtering some given variables, to
merging multiple knowledge bases. This paper first builds a relationship
between belief merging and variable forgetting by using dilation. Variable
forgetting is applied to capture belief merging operation. Finally, some new
merging operators are developed by modifying candidate variables to amend the
shortage of traditional merging operators. Different from model selection of
traditional merging operators, as an alternative approach, variable selection
in those new operators could provide intuitive information about an atom
variable among whole knowledge bases.
