Physical problem solving: Joint planning with symbolic, geometric, and dynamic constraints

July 25, 2017 Β· Declared Dead Β· πŸ› Annual Meeting of the Cognitive Science Society

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Authors Ilker Yildirim, Tobias Gerstenberg, Basil Saeed, Marc Toussaint, Josh Tenenbaum arXiv ID 1707.08212 Category cs.AI: Artificial Intelligence Cross-listed cs.RO, stat.ML Citations 23 Venue Annual Meeting of the Cognitive Science Society Last Checked 4 months ago
Abstract
In this paper, we present a new task that investigates how people interact with and make judgments about towers of blocks. In Experiment~1, participants in the lab solved a series of problems in which they had to re-configure three blocks from an initial to a final configuration. We recorded whether they used one hand or two hands to do so. In Experiment~2, we asked participants online to judge whether they think the person in the lab used one or two hands. The results revealed a close correspondence between participants' actions in the lab, and the mental simulations of participants online. To explain participants' actions and mental simulations, we develop a model that plans over a symbolic representation of the situation, executes the plan using a geometric solver, and checks the plan's feasibility by taking into account the physical constraints of the scene. Our model explains participants' actions and judgments to a high degree of quantitative accuracy.
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