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Recent advances in Artificial Intelligence (AI) have revived the quest foragents able to acquire an open-ended repertoire of skills. However, althoughthis ability is fundamentally related to the characteristics of humanintelligence, research in this field rarely considers the processes that mayhave guided the emergence of complex cognitive capacities during the evolutionof the species.  Research in Human Behavioral Ecology (HBE) seeks to understand how thebehaviors characterizing human nature can be conceived as adaptive responses tomajor changes in the structure of our ecological niche. In this paper, wepropose a framework highlighting the role of environmental complexity inopen-ended skill acquisition, grounded in major hypotheses from HBE and recentcontributions in Reinforcement learning (RL). We use this framework tohighlight fundamental links between the two disciplines, as well as to identifyfeedback loops that bootstrap ecological complexity and create promisingresearch directions for AI researchers.

Grounding Artificial Intelligence in the Origins of Human Behavior