Prioritized Logic Programming
and its Application to Commonsense Reasoning
Chiaki Sakama and Katsumi Inoue
Artificial Intelligence 123(1-2):185-222, Elsevier, 2000.
Abstract
Representing and reasoning with priorities are important in commonsense
reasoning. This paper introduces a framework of
prioritized logic programming (PLP), which has a mechanism of
explicit representation of priority information in a program.
When a program contains incomplete or indefinite information,
PLP is useful for specifying preference to reduce non-determinism in
logic programming.
Moreover, PLP can realize various forms of commonsense reasoning in AI
such as abduction, default reasoning, circumscription, and their
prioritized variants.
The proposed framework increases the expressive power of
logic programming and exploits new applications in knowledge representation.
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