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• W640679338 abstract "In this work we propose a new paradigm for the rapid learning of cause-effect relations relevant for task execution. Learning occurs automatically from action experiences by means of a novel constructive learning approach designed for applications where there is no previous knowledge of the task or world model, examples are provided on-line during run time, and the number of examples is small compared to the number of incoming experiences. These limitations pose obstacles for the existing constructivelearning methods, where on-line learning is either not considered, a significant amount of prior knowledge has to be provided, or a large number of experiences or training streams are required. The system is implemented and evaluated in a humanoid robot platform using a decision-making framework that integrates a planner, the proposed learning mechanism, and a human teacher that supports the plannerin the action selection. Results demonstrate the feasibility of the system for decision making in robotic applications." @default.
• W640679338 created "2016-06-24" @default.
• W640679338 creator A5007639805 @default.
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• W640679338 date "2010-01-01" @default.
• W640679338 modified "2023-09-26" @default.
• W640679338 title "Quick learning of cause-effects relevant for robot action" @default.
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