2024年度 人工知能学会全国大会(第38回)

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[2Q5-IS-1] Knowledge engineering

2024年5月29日(水) 15:30 〜 17:10 Q会場 (402会議室)

座長:西田 遼(産業技術総合研究所)

16:10 〜 16:30

[2Q5-IS-1-03] A Proposed Inference System for Efficient Constructive Induction

〇Taosheng Qiu1,3, Ryutaro Ichise2,1 (1. National Institute of Informatics, 2. Tokyo Institute of Technology, 3. The Graduate University for Advanced Studies, SOKENDAI)

キーワード:Constructive Induction, Inductive Logic Programming

Expressivity and scalability are the primary challenges in inductive program synthesis. While constructive synthesis frameworks may address scalability through direct access to the proof structure, the current logic programming languages are not optimized for efficient constructive inductive inference. To solve this problem, we proposed an inference system named MPL. MPL's deduction model can be relatively easily inverted, due to its use of maximum sentence size and restriction of global symbols to predicates only. In this paper, we introduce the deductive inference model of MPL and demonstrate that MPL can be utilized to simulate Cyclic Tag System, a Turing complete computational model.

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