Indexing and retrieving abstract planning knowledge
Christopher Owens · 1991
Intelligent systems can reason about plan failures and other critical planning situations by retrieving and instantiating abstract knowledge structures that characterize those situations. This approach requires a vocabulary of thematic abstractions for representing and indexing critical planning situations, and a mechanism for recognizing situations to which the thematic abstractions apply. This dissertation presents a taxonomization of critical planning situations and an abstract indexing vocabulary, both derived from the study of human planning knowledge in the form of common advice-giving proverbs. It also present a parallel, incremental model of retrieval that interleaves and integrates the processes of abstract feature detection and memory search. Together, the vocabulary and the retrieval mechanism constitute a model of memory-based reasoning about the diagnosis and repair of plan failures.