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Efficient Dialogue Using a Probabilistic Nested User Model
Date Issued
2005-08-01
Date Available
2013-07-30T11:02:29Z
Abstract
We describe a set of dialogue simulation experiments,
in which a probabilistic nested user model
is employed in deciding between speech acts for
a collaborative planning task, finding that a gain
in utility can be obtained by using a probabilistic
rather than a logical model. Given a set of ordinary
dialogue plan rules, our system generates a gametree
representation of the dialogue, using chance
nodes to represent uncertain preconditions in the
plan. Then, the game-tree is evaluated with respect
to a given user model state.
Type of Material
Conference Publication
Publisher
IJCAI
Copyright (Published Version)
2005, IJCAI
Keywords
Language
English
Status of Item
Peer reviewed
Part of
Proceedings of the Fourth IJCAI Workshop on Knowledge and Reasoning in Practical Dialogue Systems
Conference Details
The 4th IJACI Workshop on Knowledge and Reasoning in Practical Dialogue Systems, Edinburgh, Scotland, August 1, 2005
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