Learning abstract visual reasoning via task decomposition: A case study in Raven progressive matrices - Kwiatkowski, Jakub; Krawiec, Krzysztof (Zielona Góra: Uniwersytet Zielonogórski)
Learning to perform abstract reasoning often requires decomposing the task in question into intermediate subgoals that are not specified upfront, but need to be autonomously devised by the learner. In Raven progressive matrices (RPMs), the task is to choose one of the available answers given a context, where both the context and answers are composite images featuring multiple objects in various spatial arrangements. As this high-level goal is the only guidance available, learning to solve RPMs is challenging.
Keywords: abstract visual reasoning; Raven progressive matrices; machine learning; problem decomposition