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A Theory of Formalisms for Representing Knowledge
Authors
- Heng Zhang Zhejiang Lab
- Guifei Jiang Nankai University
- Donghui Quan Zhejiang Lab
DOI: https://doi.org/10.1609/aaai.v39i14.33674 Abstract 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. How to Cite
Zhang, H., Jiang, G., & Quan, D. (2025). A Theory of Formalisms for Representing Knowledge. Proceedings of the AAAI Conference on Artificial Intelligence, 39(14), 15257-15264. https://doi.org/10.1609/aaai.v39i14.33674
Issue Section
AAAI Technical Track on Knowledge Representation and Reasoning
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