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This chapter concerns the symbolic artificial intelligence (AI). Both technological and psychological AI employ the full range of AI methodologies, Good Old-Fashioned AI (GOFAI) included. The GOFAI methodology employs programmed instructions operating on formal symbolic representations. It is well suited to the binary, serial nature of the von Neumann digital computer. More accurately, evolutionary programming was initially developed within GOFAI, and is often used in a GOFAI context, although it can also be used for evolving connectionist networks. The major strengths of GOFAI are its abilities to model hierarchy and sequential order, to allow for precision in problem solving, and to represent specific propositional contents. GOFAI planning is even important in video games and Hollywood animation, for example, to prevent the virtual reality characters from bumping into one another. Invisibility is only one reason why GOFAI's successes go largely unsung.
It is shown that it follows from PFA that there is no compact scattered space of height greater than $\omega $ in which the sequential order and the scattering heights coincide.
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