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A Multiagent Approach to Teaching Complex Systems Development
Abstract
Teaching practical development of multi-agent systems (MAS) presents various difficulties. This is also the case for application areas, like multimodal dialog systems (MMD), which rely on agent technologies to provide their systems infrastructure. These areas are challenging for novices and require significant pre-requisite knowledge from both learners and educators. The authors aim to reduce these difficulties, targeting teaching towards undergraduate and postgraduate computing students from increasingly diverse educational backgrounds. The authors specify an adaptable multi-agent architecture and provide a set of general purpose agents to handle essential multimodal tasks like speech input/output, fusion and semantic analysis. They outline the design of this system and describe how it provides a framework for students to assemble complex systems and experiment with agent-level design patterns. They evaluate the usability of the resulting software and tools using the Cognitive Dimensions Framework and by examining students’ experience of using this approach in computing courses and project work.
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