Renewable energy sources like wind energy are copiously available without any limitation.
Wind turbines are used to tap the potential of wind energy, which is available in millions of …

Knowledge compilation has been emerging recently as a new direction of research for
dealing with the computational intractability of general propositional reasoning. According to …

Independence--the study of what is relevant to a given problem of reasoning--has received
an increasing attention from the AI community. In this paper, we consider two basic forms of …

We address in this paper the problem of counting the models of a propositional theory under
incremental changes to its literals. Specifcally, we show that if a propositional theory Δ is in a …

In this paper we show how tree decomposition can be applied to reasoning with first-order
and propositional logic theories. Our motivation is two-fold. First, we are concerned with how …

Consistency-based diagnosis is one of the most widely used approaches to model-based
diagnosis within the artificial intelligence community. It is usually carried out through an …

A model-based diagnosis problem occurs when an observation is inconsistent with the
assumption that the diagnosed system is not faulty. The task of a diagnosis engine is to …

Advanced machine learning techniques offer an unprecedented opportunity to increase the
accuracy of board-level functional fault diagnosis and reduce product cost through …

Abstract We propose a StochAstic Fault diagnosis AlgoRIthm, called SAFARI, which trades
off guarantees of computing minimal diagnoses for computational efficiency. We empirically …

Model-based diagnosis concerns using a model of the structure and behaviour of a system
or device in order to establish why the system or device is malfunctioning. Traditionally, little …