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Dynamic Memory. A Theory of Reminding and Learning in Computers and People - Schank R.C.

Schank R.C. Dynamic Memory. A Theory of Reminding and Learning in Computers and People - Cambridge University Press, 1982. - 250 p.
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Readers will differ in how much they like this book. It is written in a breathless style, rife with circumlocutions and ellipses It is assertive beyond the norms of the cautious, scholarly scientist. Some of these assertions are wrong, although in deference to the norms of foreword writing, I’m not going to tell you which ones they are. That would prejudice your own evaluation of Schank’s claims as you go along-and besides, I’m not sure myself (although I have some guesses) On the plus side you will find a powerfully intuitive mind turned loose on a set of fascinating questions, questions that will occupy a central place in the cognitive science of the next decade. The ideas are sweeping and important, and for every one that is wrong, there are two 01 three that aie right.
If you lie back and relax as you read, you will expose yourself to a great deal of insight. On the other hand, you may not be willing or able to do this. As I try to imagine a possible negative reaction to this book, I am reminded (sic) of a personal experience:
As a teenager, I was a camp counselor for a group of seven- and eight-year-old children. They differed among themselves, of course, on all the dimensions along which human beings can vary, but one especially noteworthy child was an intensely serious youngster named Steven. He was very bright, and very knowledgeable about things scientific, but he had trouble getting into things and enjoying himself. The counselors were continually trying to devise ways to improve the quality of Steven’s social and emotional experience.
One week my Aunt Sara, the Head Counselor, organized a breakfast hike for the children Everybody got up before dawn and hiked with flashlights up to a secret and special location known as The Ledge, a magnificent spot from which the entire horizon beyond the neighboring
hills could be seen. Soon the dawn began to break, and a great red orb appeared on the skyline. “Look, children, look,” said Aunt Sara with warmth and enthusiasm, “the sun is rising!”
Everyone fell silent, transfixed, staring eastward. Then the silence was broken by a dry, young voice. “The Sun never rises,” said Steven. “It’s the Earth that goes around the Sun.”
stai wa; tim of ] in i intc 1
One of the most frustrating and at the same time tantalizing things about working in Artificial Intelligence is that you are never done, It is even difficult after working for a long time on a book and finally completing it, to have a sense of accomplishment. It is always clear that there are many problems with what one has written. It is often less clear just where those problems are. But, it is always certain that as the ideas proposed are worked into computer programs, only their bare bones will remain the same. The substance of one’s idea is quite likely to continue to change as the experimentation points up the initial problems.
When Bob Abelson and I finished Scripts, Plans, Goals, and Understanding, we knew that the work was seriously incomplete. Our choice was to wait for it to be complete, which might have taken a very long time, or to publish it then and take the consequences. The consequences of publishing it when we did were quite pleasant actually. Many workers in psychology and other disciplines took our book in the vein that it was intended, as a set of suggestions for how experimentation might proceed.
This current work is intended in a similar vein. It had its origins in the incompleteness of Schank and Abelson. We knew, when we wrote that book, that we had not provided adequate definitions for some of the notions we were developing. In particular, we knew that the concept of a script, while intuitively attractive, needed a great deal more consideration than we had given it. The point of that work was that such knowledge structures were a natural part of language understanding. That having been shown, we left the myriad residual issues that followed from that hypothesis to others.
One of those residual issues was memory. We really did not consider the consequences of our claims with respect to memory. Fortunately, others did. I had a number of conversations with Gordon Bower and Ed Smith, two psychologists who worried about the claims we were making. At the same time, I began to get increasingly concerned about the nature
of the theory underlying the programs in oui own laboratory. It seemed that no one really had a good idea about what the theoretical limits to a script were. If it was convenient to do so, a structure was labeled a script.
While these concerns about scripts troubled me, their consequences were not grave, What was more important to me was that a number of the programs that we were developing at Yale seemed to have the problem of being too cumbersome to be of great use. We had always argued that there are no easy shortcuts in natural language processing. Understanding requires a great deal of knowledge, but humans do not crumble from the weight of their own information store. Automated data bases on the other hand, do get overwhelmed when they know too much We wanted to make sure that any understanding system we developed would be capable of acquiring, storing, and using its knowledge with some ease.
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