提出创意性反绎推理的计算系统新方向
Abductive Computational Systems: Creative Abduction and Future Directions
- 拆解反绎推理系统组件，发现现有方法多为演绎形式
- 理论与实践均难生成创造性假设，缺乏有效生成机制
- 面向艺术、设计等领域，适合研究认知计算与AI创造力的学者
反绎推理（abductive reasoning）即基于观察推断解释，在科学、设计和艺术领域常被提及，但其内涵在不同语境中差异显著。本文综述了反绎推理在认识论、科学与设计中的讨论，并分析各类计算系统如何应用该推理方式。分析表明，现有理论框架未能提供生成创造性假设的清晰模型，而计算系统大多仅实现形式化的三段论式反绎推理。通过分解反绎计算系统结构，论文指出当前系统在创造性假设生成方面存在明显不足，并提出若干未来研究方向，以推动计算系统中创意性反绎推理的发展。
原文摘要 · Abstract (English)
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.
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