Künstliche Intelligenz 29(4) - November 2015

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Zeitschriftenartikel
Open-EASE: A Cloud-Based Knowledge Service for Autonomous Learning
(KI - Künstliche Intelligenz: Vol. 29, No. 4, 2015) Tenorth, Moritz; Winkler, Jan; Beßler, Daniel; Beetz, Michael
We present Open-EASE, a cloud-based knowledge base of robot experience data that can serve as episodic memory, providing a robot with comprehensive information for autonomously learning manipulation tasks. Open-EASE combines both robot and human activity data in a common, semantically annotated knowledge base, including robot poses, object information, environment models, the robot’s intentions and beliefs, as well as information about the actions that have been performed. A powerful query language and inference tools support reasoning about the data and retrieving information based on semantic queries. In this paper, we focus on applications of Open-EASE in the context of autonomous learning.