تقرير
One-Shot Induction of Generalized Logical Concepts via Human Guidance
| العنوان: | One-Shot Induction of Generalized Logical Concepts via Human Guidance |
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| المؤلفون: | Das, Mayukh, Ramanan, Nandini, Doppa, Janardhan Rao, Natarajan, Sriraam |
| سنة النشر: | 2019 |
| المجموعة: | Computer Science |
| مصطلحات موضوعية: | Computer Science - Artificial Intelligence |
| الوصف: | We consider the problem of learning generalized first-order representations of concepts from a single example. To address this challenging problem, we augment an inductive logic programming learner with two novel algorithmic contributions. First, we define a distance measure between candidate concept representations that improves the efficiency of search for target concept and generalization. Second, we leverage richer human inputs in the form of advice to improve the sample-efficiency of learning. We prove that the proposed distance measure is semantically valid and use that to derive a PAC bound. Our experimental analysis on diverse concept learning tasks demonstrates both the effectiveness and efficiency of the proposed approach over a first-order concept learner using only examples. Comment: STARAI '20, Workshop version |
| نوع الوثيقة: | Working Paper |
| الوصول الحر: | http://arxiv.org/abs/1912.07060Test |
| رقم الانضمام: | edsarx.1912.07060 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |