モデル生成に基づく並列アブダクション

抄録

We investigate several realizations of parallel abductive reasoning systems using the model generation theorem prover MGTP. The first two methods, the "MGTP+ATMS" and "MGTP+MGTP" methods, are co-operative problem-solving architectures, in which model generation and consistency checks communicate with each other. There, parallelism is exploited by checking consistencies in parallel. However, since these systems consist of two different components, the possibilities for parallelization are limited. In contrast, the remaining two methods do not separate the inference engine from consistency checks, but realize both functions in only one MGTP that is used as a "generate-and-test" mechanism, so that consistency checks are automatically performed in reasoning processes. In these methods, multiple models can be kept in distributed memories, thus a great amount of parallelism can be obtained. In particular, we conjecture that the "Skip" method, which introduces hypotheses only when they are necessary, will be the most promising for parallel abduction. We also attempt the upside-down meta-interpretation approach for abduction, in which top-down reasoning is simulated by a bottem-up reasoner. Some evaluation of these abductive systems that are applied to planning and design problems is also described in this paper.