Representations as Control Sub-states

Since first presenting a paper criticising excessive reliance on logical representations in AI at the second IJCAI at Imperial College London in 1971, I have been trying to understand what representations are and why human beings seem to need so many different kinds, tailored to different purposes. This position paper presents the beginnings of a general answer starting from the notion that an intelligent agent is essentially a control system with multiple control states, many of which contain information (both factual and non-factual), albeit not necessarily in a propositional form. The paper attempts to give a general characterisation of the notion of the syntax of an information store, in terms of types of variation the relevant mechanisms can cope with. Different kinds of syntax can support different kinds of semantics, and serve different kinds of purposes. Similarly concepts of semantics, pragmatics and inference are generalised to apply to information-bearing sub-states in control systems. A number of common but incorrect notions about representation are criticised (such as that pictures are in some way isomorphic with what they represent), and a first attempt is made to characterise dimensions in which forms of representations can differ, including the explicit/implicit dimension.