Configuration

Abstract

Many manufacturers offer modifications of a product, along with a range of optional components and accessories.

Preferences in artificial intelligence

“…Indeed, artificial intelligence aims at producing computational artifacts that can help humans in a number of problems acting on their behalf; reasoning, explaining, learning and in general handling preferences are central issues to be tackled in any non trivial artificial intelligence system. There are several applications [203] of this research area, some already deployed in practice, including personalized and location-aware recommendation systems [58] and interactive personalized configuration systems [242].…”

Configuration Knowledge Representation and Reasoning

“…For example, a user interacting with a configurator is in the need of explanations (Junker, 2004;Sinz et al, 2007) in terms of why a solution has been identified or why no solution could be found (Falkner et al, 2011;Junker, 2004). For example, a user interacting with a configurator is in the need of explanations (Junker, 2004;Sinz et al, 2007) in terms of why a solution has been identified or why no solution could be found (Falkner et al, 2011;Junker, 2004).…”

Speeding up Derivative Configuration from Product Platforms

“…For example, reasoning engines, such as BDD libraries, SAT solvers and logic-truth maintenance systems, have been used to detect invalid derivatives (i.e., those which violate some option dependency or incompatibility) [24][25][26], to provide explanations for configuration flaws [27,28], to optimize configurations (i.e., to find configurations whose cost is less or equal than a given one) [29][30][31], etc.…”

“…A widespread approach to support the automated management of configuration models is translating them to propositional logic formulas [3,25], which are processed using off-the-self tools, such as SAT solvers [35] or BDD engines [33]. Table 3 summarizes the translations needed to encode our running example into propositional logic.…”