Proceedings:
Proceedings of the AAAI Conference on Artificial Intelligence, 12
Volume
Issue:
Qualitative and Model-Based Reasoning
Track:
Model-Based Reasoning
Downloads:
Abstract:
We develop a model-based approach to reasoning, in which the knowledge base is represented as a set of models (satisfying assignments) rather then 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 fully characterize a set of theories for which the model-based representation is compact and provides efficient reasoning. These include some 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.
AAAI
Qualitative and Model-Based Reasoning