Abstract Knowledge compilation is an AI technique for addressing computationally
demanding reasoning problems. In this paper we survey recent results in knowledge …

CONSEQUENCE FINDING ALGORITHMS Page 1 PIERRE MARQUIS CONSEQUENCE
FINDING ALGORITHMS INTRODUCTION In this section, the notion of consequence finding is …

We show that many\critically constrained" Random 3SAT knowledge bases (KBs) and other
KBs commonly used as benchmarks for propositional knowledge compilation (KC) can be …

When we encode constraints as Boolean formulas, a natural question is whether the
encoding ensures a “propagation completeness” property: is the basic unit propagation …

Automatically deriving intelligible explanations to decisions made by an AI system is a
challenging task in many cases. In this report, the stress is laid on the intelligibility issue …

Abstract Knowledge compilation is a process of adding more information to a knowledge
base in order to make it easier to deduce facts from the compiled base than from the original …

We propose a framework to compute the utility of an agreement wrt a preference set in a
negotiation process. In particular, we refer to preferences expressed as weighted formulas in …

Tractable covers are introduced as a new ap proach to equivalence-preserving compilation
of propositional knowledge bases. First, a gen eral framework is presented. Then, two …

Knowledge compilation techniques are usually applied for propositional knowledge bases.
In this article, an extension of the notion of prime implicants of a knowledge base using first …

In this paper, we are mainly concerned with consistency-based diagnoses for systems
represented in a propositional framework. Several characterizations of such diagnoses …