Allen Newell

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Allen Newell (March 19 1927July 19 1992) was an American researcher in computer science and cognitive psychology at the RAND corporation and at Carnegie Mellon University's School of Computer Science and Turing Award laureates in 1957 with Herbert Simon.


  • With the hubris common to physicists, I have always felt that I have known what good science is — it is theory cast in terms of mechanisms that describe how parts of the universe behave. With sometimes immense historical delay, these mechanisms always move towards being grounded in the larger mechanistic view of the universe. Theories always propose a view of how the universe is. They can never be effectively argued to be true, but only be brought before the bar of empirical evidence. All the modern concern for contextualism, hermeneutics and the social determination of meaning has its point, but is a mere footnote to the massive evidence for this view of science. The overwhelming success within this framework of modern biology over the last half century has provided another major confirmation, if one is needed. Someday we will get another striking confirmation from cognitive science. Though it can be argued that we are well on our way, we still have an immense distance to go. Arguments are no match for the evidence that cognitive science does not control its subject the way physics, chemistry and now biology do.

Computer Science as Empirical Inquiry: Symbols and Search (1975)


Allen Newell and Herbert Simon, 1975 Turing Award Lecture[2], Communications of the ACM 19 (3), (March 1976): p. 113–126.

  • Computer science is an empirical discipline. [...] Each new machine that is built is an experiment. Actually constructing the machine poses a question to nature; and we listen for the answer by observing the machine in operation and analyzing it by all analytical and measurement means available. Each new program that is built is an experiment. It poses a question to nature, and its behavior offers clues to an answer.
    • p. 114.
  • The Physical Symbol System Hypothesis. A physical symbol system has the necessary and sufficient means for general intelligent action.
  • Heuristic Search Hypothesis. The solutions to problems are represented as symbol structures. A physical symbol system exercises its intelligence in problem solving by search—that is, by generating and progressively modifying symbol structures until it produces a solution structure.
    • p. 120.
  • If you think there is nothing problematic or mysterious about a symbol system solving problems, then you are a child of today, whose views have been formed since mid-century. Plato (and by his account, Socrates) found difficulty understanding even how problems could be entertained, much less how they could be solved. Let me remind you of how he posed the conundrum in the Meno:
And how will you inquire, Socrates, into that which you know not? What will you put forth as the subject of inquiry? And if you find what you want, how will you ever know that this is what you did not know?
  • pp. 120-121.
  • [The] amount of search is not a measure of the amount of intelligence being exhibited. What makes a problem a problem is not that a large amount of search is required for its solution, but that a large amount would be required if a requisite level of intelligence were not applied.
    • p. 122.
  • It has been a long road from Plato's Meno to the present, but it is perhaps encouraging that most of the progress along that road has been made since the turn of the twentieth century, and a large fraction of it since the midpoint of the century. Thought was still wholly intangible and ineffable until modern formal logic interpreted it as the manipulation of formal tokens. And it seemed still to inhabit mainly the heaven of Platonic ideals, or the equally obscure spaces of the human mind, until computers taught us how symbols could be processed by machines.
    • p. 125.

Quotes about Newell

  • In joint scientific efforts extending over twenty years, initially in collaboration with J. C. Shaw at the RAND Corporation, and subsequently with numerous faculty and student colleagues at Carnegie-Mellon University, they have made basic contributions to artificial intelligence, the psychology of human cognition, and list processing.
  • Although he was somewhat anti a lot of this stuff, he was very eclectic. He was very broadminded. He realized that sooner or later there was going to be a connection between what went on in the mind and what went on in the brain. Carnegie Mellon was a big place. Newell was in favor of having people do all sorts of things there, so he was basically in favor of having someone who worked on neural nets there. He could see it coming back into fashion. Even though it wasn't what he did, and he didn't really believe in it, he had enough insight to realize that it was going to come back into fashion again... That's how I ended up at CMU. I was very impressed by the fact that Newell was open to getting somebody in an area that he didn't believe in. It's very rare to see that in academics.
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