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OPEn: An Open-ended Physics Environment for Learning Without a Task
[article]
2021
arXiv
pre-print
Humans have mental models that allow them to plan, experiment, and reason in the physical world. How should an intelligent agent go about learning such models? In this paper, we will study if models of the world learned in an open-ended physics environment, without any specific tasks, can be reused for downstream physics reasoning tasks. To this end, we build a benchmark Open-ended Physics ENvironment (OPEn) and also design several tasks to test learning representations in this environment
arXiv:2110.06912v1
fatcat:wx3eyxao7ne2jkscsp36xxumoq