Strategies for Focusing Structure-Based Theorem Proving
Motivated by the problem of query answering over multiple structured commonsense theories, we exploit graph-based techniques to improve the efficiency of theorem proving for structured theories. Theories are organized into subtheories that are minimally connected by the literals they share. We present message-passing algorithms that reason over these theories while minimizing the number of inferences done within each subtheory and the number of messages sent between subtheories. We do so using consequence finding, specializing our algorithms for the case of first-order resolution, and for batch and concurrent theorem proving. We provide an algorithm that restricts the interaction between subtheories by exploiting the polarity of literals. We attempt to minimize the reasoning within each individual partition by exploiting existing algorithms for focused incremental and general consequence finding. Finally, we propose an algorithm that compiles each subtheory into one in a reduced sublanguage. We have proven the soundness and completeness of our algorithms.