Optimizing projection in the situation calculus

Abstract

Among the most frequent reasoning tasks in the situation calculus are projection queries that query the truth of conditions in a future state of affairs. However, in long running action sequences involving thousands or millions of independent actions, solving the projection problem is complex. Existing approaches require either syntactically rewriting queries through each action that has occurred via a mechanism called regression or producing and maintaining an updated representation of the knowledge base via progression. This latter approach is often infeasible, as updating a knowledge base without loss of relevant information is not possible for many domains. This thesis introduces a new t..