Universit at Dortmund Fachbereich Informatik Lehrstuhl Viii K Unstliche Intelligenz Data Preparation for Inductive Learning in Robotics Anke Rieger Data Preparation for Inductive Learning in Robotics Anke Rieger
نویسنده
چکیده
The application of logic-based learning algorithms in real-world domains, such as robotics, requires extensive data engineering, including the transformation of numerical tabular representations of real-world data to logic-based representations, feature and concept selection, the generation of the respective descriptions, and the composition of training and test sets, which meet the requirements of the respective learning algorithms. We are developing a tool, which supports a user of inductive logic-based algorithms with handling these tasks. The tool is developed in the context of a robot navigation domain, in which di erent logic-based algorithms are applied to learn operational concepts. ( This paper will appear in the Proceedings of the IJCAI-Workshop on Data Engineering for Inductive Learning, 1995.)
منابع مشابه
Data Preparation for Inductive Learning in Robotics Anke Rieger Data Preparation for Inductive Learning in Robotics Anke Rieger
The application of logic-based learning algorithms in real-world domains, such as robotics, requires extensive data engineering, including the transformation of numerical tabular representations of real-world data to logic-based representations, feature and concept selection, the generation of the respective descriptions, and the composition of training and test sets, which meet the requirement...
متن کاملUniversit at Dortmund Fachbereich Informatik Lehrstuhl Viii K Unstliche Intelligenz Text Categorization with Support Vector Machines: Learning with Many Relevant Features Text Categorization with Support Vector Machines: Learning with Many Relevant Features
This paper explores the use of Support Vector Machines (SVMs) for learning text classiers from examples. It analyzes the particular properties of learning with text data and identi es, why SVMs are appropriate for this task. Empirical results support the theoretical ndings. SVMs achieve substantial improvements over the currently best performing methods and they behave robustly over a variety o...
متن کاملData Preparation for Inductive Learning in Robotics
The application of logic-based learning algorithms in real-world domains, such as robotics, requires extensive data engineering, including the transformation of numerical tabular representations of real-world data to logic-based representations, feature and concept selection, the generation of the respective descriptions, and the composition of training and test sets, which meet the requirement...
متن کاملLearning Action-oriented Perceptual Features for Robot Navigation
Machine learning can o er an increase in the exibility and applicability of robotics at several levels of control. In this paper, we characterize two symbolic learning tasks in the eld of robotics. We outline an approach for learning features from sensory data and for using these features to learn more complex ones. We illustrate our approach with rst experiments in the eld of navigation.
متن کاملLearning Action-oriented Perceptual Features for Robot Navigation Ls{8 Report 3
Machine learning can o er an increase in the exibility and applicability of robotics at several levels of control. In this paper, we characterize two symbolic learning tasks in the eld of robotics. We outline an approach for learning features from sensory data and for using these features to learn more complex ones. We illustrate our approach with rst experiments in the eld of navigation. 1
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 1995