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Plan Recognition in Stories and in Life
Eugene Charniak, Robert Goldman
Abstract:
Plan recognition does not work the same way in stories and in "real life" (people tend to jump to conclusions more in stories). We present a theory of this, for the particular case of how objects in stories (or in life) influence plan recognition decisions. We provide a Bayesian network formalization of a simple first-order theory of plans, and show how a particular network parameter seems to govern the difference between "life-like" and "story-like" response. We then show why this parameter would be influenced (in the desired way) by a model of speaker (or author) topic selection which assumes that facts in stories are typically "relevant".
Keywords: null
Pages: 343-351
PS Link:
PDF Link: /papers/89/
BibTex:
@INPROCEEDINGS{Charniak89,
AUTHOR = "Eugene Charniak
and Robert Goldman",
TITLE = "Plan Recognition in Stories and in Life",
BOOKTITLE = "Uncertainty in Artificial Intelligence 5 Annual Conference on Uncertainty in Artificial Intelligence (UAI-89)",
PUBLISHER = "Elsevier Science",
ADDRESS = "Amsterdam, NL",
YEAR = "1989",
PAGES = "343--351"
}
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