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Research in developmental psychology consistently shows that children explorethe world thoroughly and efficiently and that this exploration allows them tolearn. In turn, this early learning supports more robust generalization andintelligent behavior later in life. While much work has gone into developingmethods for exploration in machine learning, artificial agents have not yetreached the high standard set by their human counterparts. In this work wepropose using DeepMind Lab (Beattie et al., 2016) as a platform to directlycompare child and agent behaviors and to develop new exploration techniques. Weoutline two ongoing experiments to demonstrate the effectiveness of a directcomparison, and outline a number of open research questions that we believe canbe tested using this methodology.

Exploring Exploration: Comparing Children with RL Agents in Unified Environments