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Knowledge about required functionality of an object can be used as an effective representation for a generic object category (e.g. "chair", "cup", or "hammer"). This approach to object representation and recognition has recently become an active area of research. We explore a scenario in which a robot senses the environment to obtain an initial partial shape model of an object. If the information in this initial model is not sufficient to hypothesize a possible function for the object, then additional view(s) may be suggested. Once a possible function is hypothesized, a plan is formulated for interacting with the object to confirm that its material properties are compatible with the hypothesized function. The module for reasoning about partial shape models has been evaluated on over 200 shape models acquired from range images. The module for carrying out a function verification plan has been evaluated in a simulated environment using the ThingWorld (TW) system.