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Human behavior is powerfully guided by social and moral norms. Robots that enter human societies must therefore behave in norm-conforming ways as well. However, there is currently no cognitive, let alone computational model available of how humans represent, activate, and learn norms. We offer first steps toward such a model and apply it to the design of a norm-competent social robot. We propose a general methodology for such a design, from empirical identification of relevant norms to computational implementations of norm learning to thorough and iterative evaluation of the robot's norm compliance by means of community feedback.