تقرير
An Algebraic Approach to Learning and Grounding
| العنوان: | An Algebraic Approach to Learning and Grounding |
|---|---|
| المؤلفون: | Björklund, Johanna, Lindström, Adam Dahlgren, Drewes, Frank |
| سنة النشر: | 2022 |
| المجموعة: | Computer Science |
| مصطلحات موضوعية: | Computer Science - Computation and Language, Computer Science - Formal Languages and Automata Theory, Computer Science - Logic in Computer Science, I.2.4, I.2.7, I.2.10, I.1.3, I.2 |
| الوصف: | We consider the problem of learning the semantics of composite algebraic expressions from examples. The outcome is a versatile framework for studying learning tasks that can be put into the following abstract form: The input is a partial algebra $\alg$ and a finite set of examples $(\varphi_1, O_1), (\varphi_2, O_2), \ldots$, each consisting of an algebraic term $\varphi_i$ and a set of objects~$O_i$. The objective is to simultaneously fill in the missing algebraic operations in $\alg$ and ground the variables of every $\varphi_i$ in $O_i$, so that the combined value of the terms is optimised. We demonstrate the applicability of this framework through case studies in grammatical inference, picture-language learning, and the grounding of logic scene descriptions. Comment: Accepted to LearnAut 2022 at ICALP 2022 |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/2204.02813 |
| رقم الأكسشن: | edsarx.2204.02813 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |