A Fixpoint Definition of Dynamic Constraint Satisfaction

The existence of powerful constraint satisfaction algorithms is not the sole reason of the wide success of the CSP framework. The interest of this framework is also that it offers a generic and simple way for the modeling of real world applications. Nevertheless these applications call for tasks that often differ from a classical search for a solution. The aim of the present paper is not to provide the AI community with new and efficient algorithms, but with new requests and more generally new needs. All of them are issued from the analysis of the business needs that arise around the design and exploitation of the vehicle range at Renault, the French car manufacturer. Viewing this application as a fruitful source of research problematics for the community, we present a formalization and a theoretical study, in terms on complexity, of the series of requests risen by the application.

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“…The topic of constraint-based configuration has been dealt with by [14], [21], [18], [9], [20], [2] and [13], among others.…”

Section: Online Configurationmentioning

confidence: 99%

Constraint-based Vehicle Configuration: A Case Study

Astesana

Cosserat

Fargier

2010

2010 22nd IEEE International Conference on Tools With Artificial Intelligence

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“…Such activity constraints represent an intuitive way of encoding configuration knowledge, in particular because optional components are often found in product configuration problems. In [42], Soininen et al showed that DCSPs are favorable when compared with CSP from the perspective of modularity of the knowledge base, where modularity means that small changes in the configuration knowledge only lead to small changes in the CSP encoding. A detailed analysis of computational properties and the expressiveness of CSPs and these conditional CSPs is given in [23].…”

Section: Constraint-based Approachesmentioning

confidence: 99%

Modeling and Solving Distributed Configuration Problems: A CSP-Based Approach

Jannach

Zanker

2013

IEEE Trans. Knowl. Data Eng.

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Product configuration can be defined as the task of tailoring a product according to the specific needs of a customer. Due to the inherent complexity of this task, which for example includes the consideration of complex constraints or the automatic completion of partial configurations, various Artificial Intelligence techniques have been explored in the last decades to tackle such configuration problems. Most of the existing approaches adopt a single-site, centralized approach. In modern supply chain settings, however, the components of a customizable product may themselves be configurable, thus requiring a multisite, distributed approach. In this paper, we analyze the challenges of modeling and solving such distributed configuration problems and propose an approach based on Distributed Constraint Satisfaction. In particular, we advocate the use of Generative Constraint Satisfaction for knowledge modeling and show in an experimental evaluation that the use of generic constraints is particularly advantageous also in the distributed problem solving phase.

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“…Following the DCSP formalism proposed in [22,23], we propose to use the following form of activity constraint:…”

Section: Modeling Courseware Generation Using Dcspmentioning

confidence: 99%

Pedagogically-Driven Courseware Content Generation for Intelligent Tutoring Systems

Hadji¹,

Choi²,

Jemni³

2012

International Journal of Fuzzy Logic and Intelligent Systems

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This paper describes a novel approach to adaptive courseware generation. This approach adopts its structure from existing intelligent tutoring systems and introduces a new component called pedagogical scenario model to support pedagogical flexibility in the adaptation process of courseware generation system. The adaptation is carried out using Dynamic Constraint Satisfaction Problem framework, which is a variant of classical Constraint Satisfaction Problem, to deliver courseware tailored to individual learner. Such a framework provides a high level of expressiveness to deal with the particular characteristics of courseware generation problem. Further, it automatically designs a sound courseware satisfying the design constraints imposed by the domain, the pedagogical scenario and learner models.

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A Fixpoint Definition of Dynamic Constraint Satisfaction

Cited by 18 publications

References 5 publications

Constraint-based Vehicle Configuration: A Case Study

Constraint-based Vehicle Configuration: A Case Study

Modeling and Solving Distributed Configuration Problems: A CSP-Based Approach

Pedagogically-Driven Courseware Content Generation for Intelligent Tutoring Systems

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