It deals with the practical application of constraint networks, using automated reasoning to overcome some of the blind spots in conventional iterative design. Parametric engineering design refers to routine-level design (Brown and Chandrasekaran 1985) in which the parameters and variables describing the design object are known, and the problem is one of finding a consistent set of parameter values that conform to specified requirements. It involves converting a well-established symbolic representation of an object, consisting of a set of parameters and variables, into a specific numeric representation. This conversion involves the attachment of numeric values to the parameters and the use of analysis programs to either verify the consistency of these values or eliminate inconsistent values. Conventional methods of parametric design rely on the iterative reuse of analysis programs to converge on a satisfactory solution.
Systems Integration - A broad vision of an open architecture for the creation of intelligent systems for synthesis tasks (such as planning, design and configuration) based on the handling of "issues" and the management or maintenance of the constraints describing the product of the process. Representation - a core notion of the representation of a synthesis process and the product(s) of such processes as a set of nodes making up the process or product, along with constraints on the relationship between those nodes, a set of outstanding issues, and annotations related to these - I-N-C-A - Issues, Nodes, (Critical and Auxiliary) Constraints and Annotations. Engagement with various standards setting groups is a part of this work. User Interfaces - to understand user roles in performing collaborative activities and to provide generic modules which present the state of the processes they are engaged in, their relationships to others and the status of the artefacts/products they are working with. Applications - work in various application sectors which will seek to create generic approaches (I-Tools) for the various types of Task in which users may engage.
Neither of these terms are fundamental categories. The initial AIMS scheduling problem encompassed 29,000 discrete activities, subject to 97,000 complex metric constraints specified by AIMS applications developers. Generating feasible schedules was an essential requirement for operating the 777, potentially threatening a Boeing investment of almost 10 billion dollars. The scale and complexity of this problem were unprecedented, and there were very few applicable tools or standards. Input requirements were provided as text, with a semantics negotiated and maintained through frequent discussion.
This article presents an overview and survey of current work in case-based reasoning (CBR) integrations. There has been a recent upsurge in the integration of CBR with other reasoning modalities and computing paradigms, especially rule-based reasoning (RBR) and constraint-satisfaction problem (CSP) solving. CBR integrations with modelbased reasoning (MBR), genetic algorithms, and information retrieval are also discussed. This article characterizes the types of multimodal reasoning integrations where CBR can play a role, identifies the types of roles that CBR components can fulfill, and provides examples of integrated CBR systems. Past progress, current trends, and issues for future research are discussed.
Falkner, Andreas (Siemens AG Austria) | Friedrich, Gerhard (University of Klagenfurt) | Haselböck, Alois (Siemens AG Austria) | Schenner, Gottfried (Siemens AG Austria) | Schreiner, Herwig (Siemens AG Austria)
The development of problem solvers for configuration tasks is one of the most successful and mature application areas of artificial intelligence. The provision of tailored products, services, and systems requires efficient engineering and design processes where configurators play a crucial role. Because one of the core competencies of Siemens is to provide such highly engineered and customized systems, ranging from solutions for medium-sized and small businesses up to huge industrial plants, the efficient implementation and maintenance of configurators are important goals for the success of many departments. For more than 25 years the application of constraint-based methods has proven to be a key technology in order to realize configurators at Siemens. This article summarizes the main aspects and insights we have gained looking back over this period. In particular, we highlight the main technology factors regarding knowledge representation, reasoning, and integration which were important for our achievement. Finally we describe selected key application areas where the business success vitally depends on the high productivity of configuration processes.