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Fuzzy Logic is extended toward dynamic adaptation of the degree of fuzziness. The motivation is to explain the process of learning as joint model improvement and fuzziness reduction. A learning system with fuzzy models is introduced. Initially, the system is in a highly fuzzy state of uncertain knowledge, and it dynamically evolves into a low-fuzzy state of certain knowledge. We present an image recognition example of patterns below clutter. The paper discusses relationships to formal logic,doi:10.1142/s1793005706000300 fatcat:vf7p6ja7kjgrlobrrthwsdnpku