Data Preparation for Inductive Learning in Robotics
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 induc-tive logic-based algorithms with handling these tasks. The tool is developed in the context of a robot navigation domain, in which diierent logic-based algorithms are applied to learn operational concepts.
منابع مشابه
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
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 کاملData 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...
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