Amy M. Davis

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In this thesis, we explore two iterative improvement techniques: a heuristic hill-climbing strategy (denoted LS) and a multi-agent based search (denoted ERA). We focus our investigations on one small but challenging real-world application, which is the assignment of Graduate Teaching Assistants (GTA) to academic tasks. We design and implement the LS and ERA(More)
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