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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
mans, such as solving integrals, they have difficulty performing commonsense tasks that are easy for humans, such as understanding stories. In this Technical Forum contribution, we discuss commonsense reasoning and what makes it difficult for computers. We contend that commonsense reasoning is too hard a proble
-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
mans, such as solving integrals, they have difficulty performing commonsense tasks that are easy for humans, such as understanding stories. In this Technical Forum contribution, we discuss commonsense reasoning and what makes it difficult for computers. We contend that commonsense reasoning is too hard a proble
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
mans, such as solving integrals, they have difficulty performing commonsense tasks that are easy for humans, such as understanding stories. In this Technical Forum contribution, we discuss commonsense reasoning and what makes it difficult for computers. We contend that commonsense reasoning is too hard a proble
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