The symbolic versus connectionist "debate" in AI circles has been on for too long now: it is time we arrived at a consensus, as it were. Consider as an example that archetypal problem of AI, that of developing a chat-bot. If we took a rule-based approach, we end up with a system that is too inflexible, and which produces the kind of responses that the stuff of many jokes and much ridicule; if we were to follow the "learning" approach, we might find that certain items of vocabulary not in the training set would stymie it, leading to no response…
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Here, common-sense rules inferred from the everyday world are hard-coded into the system such that it will be able to handle any type of situation. And it is in this "extremely symbolic" approach that the worst failures of that approach will probably be seen: forget one fact, and the system crashes, with nothing to lean back on.
On the other hand, best-suited to the connectionist approach are models of the brain at the micro-level. The brain is, after all, a neural network-literally. The problem here is that we get a working model, but with very little description of what is actually going on inside, and the question begs to be asked (by connectionists, of course): why model it if it cannot be explained
The natural thought is that there must be some way the two systems can "co-operate." Consider an interesting problem, one that may seem far-fetched but which is good enough to serve as an example: that of nonsense translation, as in "English French German Suite," quoted in Gdel, Escher, Bach: An Eternal Golden Braid (Douglas Hofstadter, 1979, page 366). Here, a translation into German by Robert Scott of Lewis Carroll's Jabberwocky is presented. The English stanza
'Twas brillig, and the slithy toves
All mimsy were the borogoves,
And the mome raths outgrabe."
Gets translated into the German as
"Es Brillig war. Die schlichten Toven
Und aller-mmsige Burggoven
Die Mhmen Rth' ausgraben."
Consider "outgrabe": how would one "translate" it into German It turns out that "out" is "aus" in German, and "grab" sounds perfectly German; add to that the common German "-en" suffix, and one gets "ausgraben." Similar principles apply to the translation of all the nonsense words here.
A connectionist system would be ideally suited to "get the feel" of English and German. To anyone conversant with both languages, it is patent that "mimsy" deserves to be "translated" as "mmsige"! But "feel," as it were, simply does not exist in the connectionist paradigm.
But what about the grammar "'Twas brillig" cannot be "Es war Brillig"; it must be "Es Brillig war." (Word order.) Who is to provide these rules It should be amply clear that only a co-operation of the two paradigms can plausibly take on this task of nonsense translation, which, though not a pressing problem in the real world, is indicative.
Think, now, of a system that checks English sentences for grammatical correctness. The most obvious way to do it would be via a rule-based system, because a grammar is, after all, rules. However, this does not work in the real world. Think about the cardinal rule of English grammar, that every sentence must have a verb. How grammatically correct, then, is the sentence "Why not" And what about this perfectly grammatical sentence
Given a standard book, a recursive neural network would be able to measure with reasonable accuracy whether a sentence is grammatically correct or not. But what if the test text is in a different language of
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