A Theory of Average-Case Compilability in Knowledge Representation
Proceedings of the Eighteenth International Joint Conference on Artificial Intelligence. Pages 455-459.
Abstract
Compilability is a fundamental property of knowledge representation formalisms which captures how succinctly information can be expressed. Although many results concerning compilability have been obtained, they are all "worst-case" results. We develop a theory of average-case compilability which allows for the formal comparison and classification of knowledge representation formalisms "on average."
Hubie Chen. 2003. A Theory of Average-Case Compilability in Knowledge Representation. In Proceedings of the Eighteenth International Joint Conference on Artificial Intelligence, IJCAI-03. IJCAI, 455–459. https://ijcai.org/proceedings/2003/68
Chen, H. (2003). A Theory of Average-Case Compilability in Knowledge Representation. In Proceedings of the Eighteenth International Joint Conference on Artificial Intelligence, IJCAI-03 (pp. 455–459). IJCAI. https://ijcai.org/proceedings/2003/68
@inproceedings{ijcai2003p68,
title = {A Theory of Average-Case Compilability in Knowledge Representation},
author = {Chen, Hubie},
booktitle = {Proceedings of the Eighteenth International Joint Conference on
Artificial Intelligence, {IJCAI-03}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {Georg Gottlob},
pages = {455--459},
year = {2003},
url = {https://ijcai.org/proceedings/2003/68},
}
TY - CPAPER TI - A Theory of Average-Case Compilability in Knowledge Representation AU - Chen, Hubie T2 - Proceedings of the Eighteenth International Joint Conference on Artificial Intelligence, IJCAI-03 PB - International Joint Conferences on Artificial Intelligence PY - 2003 SP - 455 EP - 459 UR - https://ijcai.org/proceedings/2003/68 ER -Copied
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