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PackIt: A Virtual Environment for Geometric Planning

Author(s): Goyal, Ankit; Deng, Jia

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dc.contributor.authorGoyal, Ankit-
dc.contributor.authorDeng, Jia-
dc.date.accessioned2021-10-08T19:50:47Z-
dc.date.available2021-10-08T19:50:47Z-
dc.date.issued2020en_US
dc.identifier.citationGoyal, Ankit, and Jia Deng. "PackIt: A Virtual Environment for Geometric Planning." In Proceedings of the 37th International Conference on Machine Learning (2020): pp. 3700-3710.en_US
dc.identifier.issn2640-3498-
dc.identifier.urihttp://proceedings.mlr.press/v119/goyal20b/goyal20b.pdf-
dc.identifier.urihttp://arks.princeton.edu/ark:/88435/pr1sn9k-
dc.description.abstractThe ability to jointly understand the geometry of objects and plan actions for manipulating them is crucial for intelligent agents. We refer to this ability as geometric planning. Recently, many interactive environments have been proposed to evaluate intelligent agents on various skills, however, none of them cater to the needs of geometric planning. We present PackIt, a virtual environment to evaluate and potentially learn the ability to do geometric planning, where an agent needs to take a sequence of actions to pack a set of objects into a box with limited space. We also construct a set of challenging packing tasks using an evolutionary algorithm. Further, we study various baselines for the task that include model-free learning-based and heuristic-based methods, as well as search-based optimization methods that assume access to the model of the environment.en_US
dc.format.extent3700 - 3710en_US
dc.language.isoen_USen_US
dc.relation.ispartofProceedings of the 37th International Conference on Machine Learningen_US
dc.rightsFinal published version. Article is made available in OAR by the publisher's permission or policy.en_US
dc.titlePackIt: A Virtual Environment for Geometric Planningen_US
dc.typeConference Articleen_US
pu.type.symplectichttp://www.symplectic.co.uk/publications/atom-terms/1.0/conference-proceedingen_US

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