The sciences of the artificial (3rd ed.)
The sciences of the artificial (3rd ed.)
Problem-Solving Methods in Artificial Intelligence
Problem-Solving Methods in Artificial Intelligence
An interdisciplinary approach in applying fundamental concepts
Proceedings of the 10th ACM conference on SIG-information technology education
Physics in motion: an interdisciplinary project
Proceedings of the 2011 conference on Information technology education
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As tools for design get increasingly complex and powerful, it is increasingly important that their users have a solid grounding in what it is these tools do and how they do it. When these tools are software engineering tools, we can assume that their users have formal training in computing. However, when the tools are for designing art or multimedia objects, the artists using the tools typically don't have much background in the computing technology they are using. While interdisciplinary design teams can work around the shortcomings of individual team members, they might be more effective teams if they shared a common language and understanding of certain key aspects of the design process. At the University of Washington we have begun a project to study the use of the theory of problem solving as shared knowledge by design teams engaged in creating of multimedia games. The theory we used is derived from early work in artificial intelligence. The concepts of state space, search, operators and evaluation functions are key components of the shared knowledge. The theory is embodied in a software system called T-STAR (Transparent STate-spaces search ARchitecture) which supports a collaborative interface for problem-solving. A key question for the project is "to what extent will interdisciplinary design teams adopt and exploit the theory of problem solving when given an opportunity to do so?"