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We wish to be able to say for some principled and not merely pragmatic reasons that some components of the cognitive system are more accurately described in biological (and ultimately physical) terms, while others demand a computational description. And we would like this distinction to coincide with the one between analog and digital. (Demopoulos, 1987, 83) The issue is within what class of systems should a description of intelligent systems be sought. On one side were those who, following the lead of physical science and engineering, adopted sets of continuous variables as the underlying state descriptions. They adopted a range of devices for expressing the laws - differential equations, excitatory and inhibitory networks, statistical and probabilistic systems. Although there were important differences between these types of laws, they all shared the use of continuous variables. The other side adopted the programming system itself as the way to describe intelligent systems. This has come to be better described as the class of symbolic systems, that is, systems whose state is characterized by a set of symbols and their associated data structures. But initially, it was simply the acceptance of programs per se as the theoretical medium. (Newell, 1983, 198)