PackIt：一个几何规划的虚拟环境
PackIt: A Virtual Environment for Geometric Planning
摘要：
共同理解物体的几何形状并计划操纵它们的行动的能力对于智能代理至关重要。我们把这种能力称为几何规划。最近，许多交互式环境已被提出来评估智能代理的各种技能，但是，他们都没有满足几何规划的需要。我们提出PackIt，一个虚拟环境来评估和潜在地学习做几何规划的能力，其中代理需要采取一系列行动来将一组对象打包到空间有限的盒子中。我们还构建了一套具有挑战性的包装任务，使用进化算法。此外，我们还研究了任务的各种基线，包括基于无模型学习和基于搜索的方法，以及基于搜索的优化方法，这些方法假设可以访问环境模型。代码和数据可在https://github.com/princeton-vl/PackIt上获得。
英文摘要：
The 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. Code and data are available at https://github.com/princeton-vl/PackIt.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
