Computing the Scope of Applicability for Acquired Task Knowledge in
  Experience-Based Planning Domains
  Experience-based planning domains have been proposed to improve problem
solving by learning from experience. They rely on acquiring and using task
knowledge, i.e., activity schemata, for generating solutions to problem
instances in a class of tasks. Using Three-Valued Logic Analysis (TVLA), we
extend previous work to generate a set of conditions that determine the scope
of applicability of an activity schema. The inferred scope is a bounded
representation of a set of problems of potentially unbounded size, in the form
of a 3-valued logical structure, which is used to automatically find an
applicable activity schema for solving task problems. We validate this work in
two classical planning domains.
