Distributed Constraint Optimization (DCOP) is a general framework that can model complex problems in multi-agent systems. Several current algorithms that solve general DCOP instances, including ADOPT and DPOP, arrange agents into a traditional pseudotree structure. We introduce an extension to the DPOP algorithm that handles an extended set of pseudotree arrangements. Our algorithm correctly solves DCOP instances for pseudotrees that include edges between nodes in separate branches. The algorithm also solves instances with traditional pseudotree arrangements using the same procedure as DPOP.We compare our algorithm with DPOP using several metrics including the induced width of the pseudotrees, the maximum dimensionality of messages and computation, and the maximum sequential path cost through the algorithm. We prove that for some problem instances it is not possible to generate a traditional pseudotree using edge-traversal heuristics that will outperform a cross-edged pseudotree. We use multiple heuristics to generate pseudotrees and choose the best pseudotree in linear space-time complexity. For some problem instances we observe significant improvements in message and computation sizes compared to DPOP.
A major challenge for broadening participation in computing within K-12 settings is the lack of trained teachers. While professional development programs provide opportunities for the development of knowledge, skills, and pedagogy in teaching computing, teachers need ongoing support throughout the academic year. In this paper, we describe a course-based model for partnering undergraduates with teachers and students in a field experience model. We describe the model focusing on learning objectives, curriculum, field component and partnership building. We subsequently report on the products that undergraduates were able to create with their partner teachers. Finally, we investigate the impact of the field experience model on undergraduates' content knowledge, pedagogical skills and career development.
We report on the preliminary results of an ongoing study examining the teaching of new primary school topics based on Computational Thinking in New Zealand. We analyse detailed feedback from 13 teachers participating in the study, who had little or no previous experience teaching computer science and related topics. From this we extract key themes identified by the teachers that are likely to be encountered deploying a new curriculum, including unexpected opportunities for cross-curricula learning, development of social skills, and engaging a wide range of students.
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