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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
trument these components so that the reflective layers of the architecture had useful information available to them. He contrasted the Soar project (Laird, Newell, and Rosenbloom 1987) as an effort to eliminate and unify components rather than to accumulate and diversify them, as in the Minsky- Sloman
-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
trument these components so that the reflective layers of the architecture had useful information available to them. He contrasted the Soar project (Laird, Newell, and Rosenbloom 1987) as an effort to eliminate and unify components rather than to accumulate and diversify them, as in the Minsky- Slam= p
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
trument these components so that the reflective layers of the architecture had useful information available to them. He contrasted the Soar project (Laird, Newell, and Rosenbloom 1987) as an effort to eliminate and unify components rather than to accumulate and diversify them, as in the Minsky- Sloman
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