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it shouldn't keep failing while learning until it gets it right.
I've looked into it a while back. My work is (vaguely) dealing with something that comes right before behavioural robotics: we are working on adaptation and rapid learning for a specific context at the moment. The idea being: if the robot has a learned representation from experience, cool, it should use it. but if it doesn't, it shouldn't keep failing while learning until it gets it right. MIKE
This way, learning doesn't *enable* performance, it *enhances* it.
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