Abductive Computational Systems: Creative Abduction and Future Directions
This is an incremental review paper that identifies gaps in computational systems for creative abductive reasoning, relevant for researchers in AI and computational creativity.
This paper analyzes how abductive reasoning is discussed across epistemology, science, and design, and examines computational implementations, finding that neither theoretical frameworks nor existing systems adequately address generating creative hypotheses. The authors break down abductive computational systems into components and identify specific directions for future research to advance creative abductive reasoning.
Abductive reasoning, reasoning for inferring explanations for observations, is often mentioned in scientific, design-related and artistic contexts, but its understanding varies across these domains. This paper reviews how abductive reasoning is discussed in epistemology, science and design, and then analyses how various computational systems use abductive reasoning. Our analysis shows that neither theoretical accounts nor computational implementations of abductive reasoning adequately address generating creative hypotheses. Theoretical frameworks do not provide a straightforward model for generating creative abductive hypotheses, computational systems largely implement syllogistic forms of abductive reasoning. We break down abductive computational systems into components and conclude by identifying specific directions for future research that could advance the state of creative abductive reasoning in computational systems.