Abstract

The vast majority of work in machine vision emphasizes the representation of perceived objects and events: it is these internal representations that incorporate the `knowledge' in knowledge-based vision or form the `models' in model-based vision. In this paper, we discuss simple machine vision systems developed by artificial evolution rather than traditional engineering design techniques, and note that the task of identifying internal representations within such systems is made difficult by the lack of an operational definition of representation at the causal mechanistic level. Consequently, we

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