arXiv 2012.085642020-12-17cs.AI

将人工智能根植于人类行为的起源

Grounding Artificial Intelligence in the Origins of Human Behavior

Inria（法国国家信息与自动化研究所）；Ensta ParisTech（巴黎高等先进技术学院）

Eleni Nisioti, Clément Moulin-Frier

摘要：

人工智能（AI）的最新进展重新唤起了对能够获得开放式技能库的智能体的追求。然而，尽管这种能力从根本上与人类智力的特征有关，但该领域的研究很少考虑在物种进化过程中可能指导复杂认知能力出现的过程。人类行为生态学（HBE）的研究旨在了解人类本性的行为如何被视为对我们生态位结构的重大变化的适应性反应。在本文中，我们提出了一个框架，强调环境复杂性在开放式技能获取中的作用，基于HBE的主要假设和强化学习（RL）的最新贡献。我们使用这个框架来突出这两个学科之间的基本联系，并确定引导生态复杂性的反馈回路，为人工智能研究人员创造有前途的研究方向。

英文摘要：

Recent advances in Artificial Intelligence (AI) have revived the quest for agents able to acquire an open-ended repertoire of skills. However, although this ability is fundamentally related to the characteristics of human intelligence, research in this field rarely considers the processes that may have guided the emergence of complex cognitive capacities during the evolution of the species. Research in Human Behavioral Ecology (HBE) seeks to understand how the behaviors characterizing human nature can be conceived as adaptive responses to major changes in the structure of our ecological niche. In this paper, we propose a framework highlighting the role of environmental complexity in open-ended skill acquisition, grounded in major hypotheses from HBE and recent contributions in Reinforcement learning (RL). We use this framework to highlight fundamental links between the two disciplines, as well as to identify feedback loops that bootstrap ecological complexity and create promising research directions for AI researchers.

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。

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