Reasoning with Models
Abstract
We develop a model-based approach to reasoning, in which the knowledge base is represented as a set of models (satisfying assignments) rather than a logical formula, and the set of queries is restricted. We show that for every propositional knowledge base (KB) there exists a set of characteristic models with the property that a query is true in KB if and only if it is satisfied by the models in this set. We characterize a set of functions for which the model-based representation is compact and provides efficient reasoning. These include cases where the formula-based representation does not support efficient reasoning. In addition, we consider the model-based approach to abductive reasoning and show that for any propositional KB, reasoning with its model-based representation yields an abductive explanation in time that is polynomial in its size. Some of our technical results make use of the Monotone Theory, a new characterization of Boolean functions recently introduced. The notion of ...
Cite
Text
Khardon and Roth. "Reasoning with Models." AAAI Conference on Artificial Intelligence, 1994.Markdown
[Khardon and Roth. "Reasoning with Models." AAAI Conference on Artificial Intelligence, 1994.](https://mlanthology.org/aaai/1994/khardon1994aaai-reasoning/)BibTeX
@inproceedings{khardon1994aaai-reasoning,
title = {{Reasoning with Models}},
author = {Khardon, Roni and Roth, Dan},
booktitle = {AAAI Conference on Artificial Intelligence},
year = {1994},
pages = {1148-1153},
url = {https://mlanthology.org/aaai/1994/khardon1994aaai-reasoning/}
}