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Abstract:
To be effective in many HCI uses, a computational cognitive model must behave like a human, not simply get the job done with the least effort or in the least time. Building computational models that emulate human behavior on complex tasks is an ambitious undertaking, as they must include perception and motor behavior as well as problem-solving, learning and large amounts of knowledge. This project demonstrates that building a complex model of perception, cognition and motor behavior can be accomplished by re-using architectures and models of component capabilities built for other tasks. It also demonstrates how emergent properties of such a complex model can reveal important insights for cognitive science.