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A framework for the abstraction of motion concepts from sequences of images by computer is presented. The framework includes: 1) representation of knowledge for motion concepts that is based on semantic networks; and 2) associated algorithms for recognizing these motion concepts. These algorithms implement a form of feedback by allowing competition and cooperation among local hypotheses. They also allow a change of attention mechanism that is based on similarity links between knowledge units, and a hypothesis ranking scheme based on updating of certainty factors that reflect the hypothesis set inertia. The framework is being realized with a system called ALVEN. The purpose behind this system is to provide an evolving research prototype for experimenting with the analysis of certain classes of biomedical imagery, and for refining and quantifying the body of relevant medical knowledge.