My work on a senior honors thesis at UCB on simulated neural nets got me interested in complex systems generally, and the problem of how best to represent them. I developed a new way to represent rules that was published in Communications of the ACM in 1995. This work led me also to try to understand the role that abstractions, as reified by notational systems, play in both facilitating and limiting cognition. I started a Notational Engineering Laboratory at George Washington University, and guest-edited a special issue on notational engineering of the journal Semiotica in 1999. I continue to work on these areas today, after retiring several years ago, in hopes of completing readily understandable books about how we could better represent rules in particular and new abstractions generally via the comparative and historical study of diverse notational systems.
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