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An Ontology-based Multi-level Robot Architecture for Learning from Experiences

Sebastian Rockel, Bernd Neumann, Jianwei Zhang, Sandeep Krishna Reddy Dubba, Anthony G. Cohn, Štefan Konečný, Masoumeh Mansouri, Federico Pecora, Alessandro Saffiotti, Martin Günther, Sebastian Stock, Joachim Hertzberg, Ana Maria Tomé, Armando J. Pinho, Luís Seabra Lopes, Stephanie von Riegen, Lothar Hotz

Year
2013
Citations
31

Abstract

One way to improve the robustness and flexibility of robot performance is to let the robot learn from its experiences. In this paper, we describe the architecture and knowledge-representation framework for a service robot being developed in the EU project RACE, and present examples illustrating how learning from experiences will be achieved. As a unique innovative feature, the framework combines memory records of low-level robot activities with ontology-based high-level semantic descriptions. 1

Keywords

Computer scienceRobotRobustness (evolution)OntologyArtificial intelligenceArchitectureFlexibility (engineering)Service robotRobot learningRepresentation (politics)

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