Generating Discourse across Several User Models: Maximizing Belief while Avoiding Boredom and Overload
Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence. Natural Language. Pages 1251-1258.
Abstract
In this paper we present a content planning system which takes into consideration a user 's boredom and cognitive overload. Our system applies a constraint-based optimization mechanism which maximizes a probabilistic function of a user's beliefs, and uses a representation of boredom and overload as constraints that affect the possible values of this function . Further, we discuss two orthogonal policies for relaxing the parameters of the communication process when these constraints are violated: conveying less ·information or breaking up the material into smaller chunks.
@inproceedings{ijcai1995p161,
title = {Generating Discourse across Several User Models: Maximizing Belief while Avoiding Boredom and Overload},
author = {Zukerman, Ingrid and McConachy, Richard},
booktitle = {Proceedings of the Fourteenth International Joint Conference on
Artificial Intelligence, {IJCAI-95}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {Chris S. Mellish},
pages = {1251--1258},
year = {1995},
note = {Natural Language},
url = {https://ijcai.org/proceedings/1995/161},
}
TY - CPAPER TI - Generating Discourse across Several User Models: Maximizing Belief while Avoiding Boredom and Overload AU - Zukerman, Ingrid AU - McConachy, Richard T2 - Proceedings of the Fourteenth International Joint Conference on Artificial Intelligence, IJCAI-95 PB - International Joint Conferences on Artificial Intelligence PY - 1995 SP - 1251 EP - 1258 UR - https://ijcai.org/proceedings/1995/161 ER -Copied
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