Uncertainty in Artificial Intelligence
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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:
Pages: 54-59
PS Link:
PDF Link: /papers/89/p54-charniak.pdf
BibTex:
@INPROCEEDINGS{Charniak89,
AUTHOR = "Eugene Charniak and Robert Goldman",
TITLE = "Plan Recognition in Stories and in Life",
BOOKTITLE = "Proceedings of the Fifth Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-89)",
PUBLISHER = "AUAI Press",
ADDRESS = "Corvallis, Oregon",
YEAR = "1989",
PAGES = "54--59"
}


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