AIE volume 23 issue 4 Cover and Back matter

2009 Artificial intelligence for engineering design, analysis and manufacturing  
This Special Issue of AI EDAM will be devoted to papers concerned with biologically inspired design. Natural processes have led to the development of a plethora of biological systems that carry out a multitude of tasks in a highly resource-effective way within a variety of environments and constraints. Many of these tasks, environments, and constraints are similar to those relevant in engineering design. Therefore, biological systems offer a rich, potential source of inspiration for novel and
more » ... source-effective engineering designs. History shows ample anecdotal evidence of using these systems as inspiration for engineering. Biologically inspired designs were previously an outcome of individual interest or accidental exposure, but supporting their use in inspiring engineering design is rapidly developing into an area of active research and exploration. This Special Issue is aimed at providing a state-of-the-art collection of research outcomes in this emerging area. Although papers with normal AI content are desired, for this Special Issue we broaden the scope to include papers that provide knowledge and associated methodology for biologically inspired design. Suitable topics include, but are not limited to, the following: † models, techniques, or systems, both human-centered and computational, for (supporting) biologically inspired design (including biomimetics/biomimicry/bionics); † models of reasoning for biologically inspired design; and † studies of reasoning for biologically inspired design. All submissions will be anonymously reviewed by at least three expert reviewers. The selection for publication will be made on the basis of these reviews. Information about the format and style required for AI EDAM papers can be found at Configuration can be defined as the composition of a complex product from instances of a set of component types, taking into account restrictions on the compatibility of those component types. From the viewpoint of product configuration, different artificial intelligence (AI) approaches are well established as central technologies in industrial configuration systems. However, the wide use of configuration technologies and the increasing size and complexity of configuration problems in industry makes the field more challenging than ever. Nowadays, the mass customization paradigm is extended from traditional physical products to the fields of software and service configuration. Traditional configuration systems have evolved into interactive Web-based applications that need to support highly sophisticated preference handling and explanation techniques. In addition to the configuration of physical products, real-world applications of configuration technologies are also encountered in domains such as computational biology, service composition, design, image analysis, model-driven software engineering, and software product lines. The ever increasing range of real-world applications triggers the demand to extend existing configurator functionalities. A wide range of AI techniques provide major contributions in this context: constraint satisfaction, description logics, logic programming, case-based reasoning, learning, knowledge acquisition, intelligent testing, and different specialized problem solving methods. As a successful AI application area, configuration has attracted lasting industrial interest and renewed research, as demonstrated by recent workshops on configuration at IJCAI this Special Issue on configuration is to demonstrate novel and innovative configuration research as well as new industrial applications of configuration technologies. We encourage submissions describing novel results involving AI in configuration-related areas, which may include, but are not limited to, the following: † theoretical issues justified by practical concerns; † methods for computing configurations and supporting configuration tasks; † methods for effective configuration knowledge base development, testing, and debugging; † configuration and product and service design, product and service life cycle management, and production management; † thorough case studies highlighting new practical problems, needs, and experiences; and † practical and new applications based on a well-defined theory or model. Articles that survey different approaches and thoroughly analyze their differences and commonalities are also welcome. Papers will be anonymously reviewed by at least two reviewers. Quality papers not selected for this Special Issue may be considered for standard publication in AI EDAM.
doi:10.1017/s0890060409990084 fatcat:geaq6oohcjhjzg4qgodzid2akm