Extending planning knowledge using ontologies for goal opportunities
  Approaches to goal-directed behaviour including online planning and
opportunistic planning tackle a change in the environment by generating
alternative goals to avoid failures or seize opportunities. However, current
approaches only address unanticipated changes related to objects or object
types already defined in the planning task that is being solved. This article
describes a domain-independent approach that advances the state of the art by
extending the knowledge of a planning task with relevant objects of new types.
The approach draws upon the use of ontologies, semantic measures, and ontology
alignment to accommodate newly acquired data that trigger the formulation of
goal opportunities inducing a better-valued plan.
