Overview

OLYMPUS DIGITAL CAMERA

Configuration can be interpreted as a special type of design approach where the product being configured is composed from instances of a set of predefined component types that can be combined in ways defined by a set of constraints. This task requires powerful knowledge representation formalisms and acquisition methods to capture the variety and complexity of configurable products. Furthermore, efficient reasoning methods are required to support intelligent interactive behavior, solution search, satisfaction of user preferences, personalization, optimization, reconfiguration, and diagnosis.

The main goal of the workshop is to promote high-quality research in all technical areas related to configuration. The workshop is of interest for both, researchers working in the various fields of Artificial Intelligence mentioned below as well as for industry representatives interested in the relationship between configuration technology and the business problem behind configuration and mass customization. It provides a forum for the exchange of ideas, evaluations, and experiences especially related to the use of AI techniques in the configuration context.

Workshop topics include but are not limited to the following ones:

  1. Configuration Problems and Models
    Structure of configuration problems, knowledge representation, ontologies, fuzzy and incomplete knowledge, standardization of catalog exchange formats, feature models, configuration problems, representations for product and process configuration, product design and configuration.
  2. Techniques for obtaining and/or maintaining Configuration Models
    Knowledge acquisition methods, cognitive approaches, machine learning, data extraction methods, ontology integration, reconciliation of knowledge bases, knowledge elicitation, testing and debugging, knowledge understanding.
  3. Reasoning Methods
    Constraint satisfaction problems and extensions, preference based reasoning, description logics, rules, case-based reasoning, SAT-solving, local search, genetic algorithms, neural networks, problem decomposition, optimization, multi-criteria optimization, symmetry breaking, cooperative configuration processes, reconfiguration of existing systems, explanations, distributed problem solving, benchmark proposals, knowledge-based recommendation, knowledge compilation.
  4. Intelligent User Interfaces and Business Process Integration
    Personalization, machine learning, explanations, recommender technologies, configuration web services, related software architectures, distributed configuration, integration into the production and selling process, configuration and mass customization.
  5. Applications and Tools
    Configuration tools, design tools, application reports, case studies, real-world challenges, test environments for configuration knowledge bases, configuration in related fields such as software configuration, service composition, and model-driven engineering, environments for feature model development and maintenance.