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Explanation-based Learning from Mobile Robot Perception (EBNN)
This project is no longer active.
Head: Tom Mitchell
Mailing address:
Carnegie Mellon University
Robotics Institute
5000 Forbes Avenue
Pittsburgh, PA 15213
For more information, see this project's homepage.
Explanation-based neural network learning (EBNN) has recently been introduced as a method for reducing the amount of training data required for reliable generation, by relying instead on approximate, previously learned knowledge. We are conducting first experiments applying EBNN to the problem of learning object recognition for a mobile robot. In these experiments, Xavier traveling down a hallway corridor learns to recognize distant doors based on color camera images and sonar sensations.