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Approaches to goal-directed behaviour including online planning andopportunistic planning tackle a change in the environment by generatingalternative goals to avoid failures or seize opportunities. However, currentapproaches only address unanticipated changes related to objects or objecttypes already defined in the planning task that is being solved. This articledescribes a domain-independent approach that advances the state of the art byextending the knowledge of a planning task with relevant objects of new types.The approach draws upon the use of ontologies, semantic measures, and ontologyalignment to accommodate newly acquired data that trigger the formulation ofgoal opportunities inducing a better-valued plan.

Extending planning knowledge using ontologies for goal opportunities