提出统一框架证明多数知识表示形式本质相同
A Theory of Formalisms for Representing Knowledge
- 构建通用框架统合多种知识表示形式
- 证明所有通用形式递归同构,等价于同一系统
- 适合关注知识表示理论的学者与系统设计者
人工智能领域长期存在知识表示形式优劣之争。从声明式与过程式之争,到符号主义与连接主义之争,核心在于知识是显式表达(如逻辑理论)还是隐式编码(如深度学习参数)。本文提出一个通用框架,用以捕捉各类知识表示形式。在该框架下,我们发现一类普适性知识表示形式,并证明所有普适形式均递归同构。此外,我们还证明:所有具备填充性质且可相互转化的形式也递归同构。这表明,经离线编译后,所有普适(或自然且等价)的知识表示形式本质上是相同的,为上述争议提供了部分解答。
原文摘要 · Abstract (English)
There has been a longstanding dispute over which formalism is the best for representing knowledge in AI. The well-known "declarative vs. procedural controversy" is concerned with the choice of utilizing declarations or procedures as the primary mode of knowledge representation. The ongoing debate between symbolic AI and connectionist AI also revolves around the question of whether knowledge should be represented implicitly (e.g., as parametric knowledge in deep learning and large language models) or explicitly (e.g., as logical theories in traditional knowledge representation and reasoning). To address these issues, we propose a general framework to capture various knowledge representation formalisms in which we are interested. Within the framework, we find a family of universal knowledge representation formalisms, and prove that all universal formalisms are recursively isomorphic. Moreover, we show that all pairwise intertranslatable formalisms that admit the padding property are also recursively isomorphic. These imply that, up to an offline compilation, all universal (or natural and equally expressive) representation formalisms are in fact the same, which thus provides a partial answer to the aforementioned dispute.
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