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iven Understanding: An Integrated Theory of Story Understanding, Memory, and Learning, Technical Report YALE/DCS(tr710, Computer Science Department. Yale University, New Haven, CT (1989). (15.) C. Dolan, Tensor Manipulation Networks: Connectionist and Symbolic Approaches to Comprehension, Learning, and Planning
w to represent, organize, and use much of commonsense knowledge, let alone build a machine that could learn all of that automatically on its own. As John McCarthy noted long ago: "in order for a program to be capable of learning something, it must first be able to represent that knowledge." There arc very few
-Driven Understanding: An Integrated Theory of Story Understanding, Memory, and Learning, Technical Report YALVDCS4710, Computer Science Department, Yale University, New Haven, CT (1989). (15.) C. Dolan, Tensor Manipulation Networks: Connectionist and Symbolic Approaches to Comprehension, Learning, and Planning
w to represent, organize, and use much of commonsense knowledge, let alone build a machine that could learn all of that automatically on its own. As John McCarthy noted long ago: "in order for a program to be capable of learning something, it must first be able to represent that knowledge? There are very few
iven Understanding: An Integrated Theory of Story Understanding, Memory, and Learning, Technical Report YALE/DCSitr710, Computer Science Department, Yale University, New Haven, CT (1989). (15.) C. Dolan, Tensor Manipulation Networks: Connectionist and Symbolic Approaches to Comprehension, Learning, and Planning
w to represent, organize, and use much of commonsense knowledge, let alone build a machine that could learn all of that automatically on its own. As John McCarthy noted long ago: "in order for a program to be capable of learning something, it must first be able to represent that knowledge." There are very few
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