Preferences for Model Selection in Explanation
Proceedings of the Thirteenth International Joint Conference on Artificial Intelligence. Natural Language. Pages 1208-1214.
Abstract
The range of possible domain models on which an explanation can be based is often large, yet human explainers are able to choose models that addres~ a questioner's informative needs without undue obscunty. However few existing explanation systems use knowledge bases providing multiple models of ~eir topics of explanation let alone account for the selectton of a model for a given explanation. This paper demonstrates the utility of a preference-based mechanism for model selection. Selection heuristics are made explicit as preferences and can be added, modified, or removed without modifying the interpreter or other planning knowledge. The mechanism is more general than previous mechanisms for model selection or "perspective,,. and can apply previously identified model selection criteria.
@inproceedings{ijcai1993p167,
title = {Preferences for Model Selection in Explanation},
author = {Suthers, Daniel D.},
booktitle = {Proceedings of the Thirteenth International Joint Conference on
Artificial Intelligence, {IJCAI-93}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {Ruzena Bajcsy},
pages = {1208--1214},
year = {1993},
note = {Natural Language},
url = {https://ijcai.org/proceedings/1993/167},
}
TY - CPAPER TI - Preferences for Model Selection in Explanation AU - Suthers, Daniel D. T2 - Proceedings of the Thirteenth International Joint Conference on Artificial Intelligence, IJCAI-93 PB - International Joint Conferences on Artificial Intelligence PY - 1993 SP - 1208 EP - 1214 UR - https://ijcai.org/proceedings/1993/167 ER -Copied
Machine-readable versions of this paper, for tools and AI agents:
