Logical Versus Analogical or Symbolic Versus Connectionist or Neat Versus Scruffy
AbstractEngineering and scientific education condition us to expect everything, including intelligence, to have a simple, compact explanation. Accordingly, when people new to AI ask "What's AI all about," they seem to expect an answer that defines AI in terms of a few basic mathematical laws. Today, some researchers who seek a simple, compact explanation hope that systems modeled on neural nets or some other connectionist idea will quickly overtake more traditional systems based on symbol manipulation. Others believe that symbol manipulation, with a history that goes back millennia, remains the only viable approach. Marvin Minsky subscribes to neither of these extremist views. Instead, he argues that AI must use many approaches. AI is not like circuit theory and electromagnetism. There is nothing wonderfully unifying like Kirchhoff's laws are to circuit theory or Maxwell's equations are to electromagnetism. Instead of looking for a "right way," the time has come to build systems out of diverse components, some connectionist and some symbolic, each with its own diverse justification." - Patrick Winston
How to Cite
Minsky, M. L. (1991). Logical Versus Analogical or Symbolic Versus Connectionist or Neat Versus Scruffy. AI Magazine, 12(2), 34. https://doi.org/10.1609/aimag.v12i2.894
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