Learning to Understand by Evolving Theories
- In this paper, we describe an approach that enables an autonomous system to infer the semantics of a command (i.e. a symbol sequence representing an action) in terms of the relations between changes in the observations and the action instances. We present a method of how to induce a theory (i.e. a semantic description) of the meaning of a command in terms of a minimal set of background knowledge. The only thing we have is a sequence of observations from which we extract what kinds of effects were caused by performing the command. This way, we yield a description of the semantics of the action and, hence, a definition.
Document Type: | Preprint |
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Language: | English |
Author: | Martin E. Müller, Madhura D. Thosar |
ArXiv Id: | http://arxiv.org/abs/1307.7303 |
Publisher: | arXiv |
Date of first publication: | 2013/07/27 |
Note: | KRR Workshop at ICLP 2013 |
Departments, institutes and facilities: | Fachbereich Informatik |
Dewey Decimal Classification (DDC): | 0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik |
Entry in this database: | 2015/04/02 |