Abstract
It is frequently pointed out that a tabula rasa learning system needs constraints in order to extract structural information from its input-output sequence. We have been experimenting with a learning-system (PP) that incorporates a simple associative form of learning in a production system architecture. It is demonstrated that PP, implemented in a simulated robot, can learn the structure of a multi-level task with the help of speech and one or more auxiliary actions. Following a suggestion that structure could be acquired by a stress/nonstress distinction in the teacher's verbal presentation, we report briefly on an experiment that shows that stress can replace the auxiliary action.
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