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Baylor Wetzel

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2 papers

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AAAI Conference 2012 Conference Paper

Effects of Representation on Solving Complex Spatial-Temporal Problems

Baylor Wetzel

Human data are used to study how people solve complex problems that have spatial and temporal components. Major findings include the use of task-focused representations, unexpectedly tight coupling of representation and search, time and space conflation, and use of multiple concurrent representations. The major contributions of this work include a set of abstract representations that strongly support spatial-temporal reasoning.

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IJCAI Conference 2011 Conference Paper

Transfer Learning in Spatial Reasoning Puzzles

Baylor Wetzel

Previous work on transfer learning focused on adapting solutions in a base domain to problems with similiar features or structure in a new domain. Different techniques are required for domains where problems are qualitatively dissimilar in both features and structures. In this work, we examine how transfer learning might be accomplished in the domain of "tower defense" spatial reasoning puzzles. Using a combination of human studies and generative computer models, we show that transfer is possible in this domain by using a set of strategies, possibly in a novel combination, inferred from multiple base problems.

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