I have to post this as well:pic.twitter.com/Lh9FxmJl6k
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I found it very important to learn basics of LISP to start understanding symbolic AI literature. It seems like this programming language for many decades structured the way people thought and communicated with each other.
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Clojure is also a practical lisp :)
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Fair enough. I meant a LISP, not the LISP. In fact, I went for Scheme.
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Indeed, LISP was very influential in people's thinking about symbolic AI. For example, Allen Newell described his "paradigmatic symbol system" as a "Lisp-ish kind of beast".
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I guess you are talking about the essential symbol system in his paper "Physical Symbol Systems", 1980? I have just read this paper, and I found it quite interesting, but also very very hard to follow. I'd be curious to know if similar ideas were ever explained better.
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Reading an intro to Common Lisp or Haskell, even if it has no bearing on the sort of work you think you’ll do, is mentally refreshing.
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I'd go with Scheme rather than Common Lisp.
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This is a pretty good LISP reference, Peter Norvig’s open-source repository, "Paradigms of Artificial Intelligence Programming: Case Studies in Common Lisp"https://github.com/norvig/paip-lisp …
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The classic SICP is an CS 101 book that uses Scheme, a cleaned up dialect of Lisp. Many people praised its elegance. https://en.wikipedia.org/wiki/Structure_and_Interpretation_of_Computer_Programs …
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The way the language is structured also makes it quite convenient for genetic algorithms too
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