Physical problem solving: Joint planning with symbolic, geometric, and dynamic constraints
July 25, 2017 Β· Declared Dead Β· π Annual Meeting of the Cognitive Science Society
"No code URL or promise found in abstract"
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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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