对偶(语法数字)
心理学
结果(博弈论)
动作(物理)
价值(数学)
强化学习
行动理论(社会学)
社会心理学
认知
代表(政治)
认识论
认知科学
认知心理学
计算机科学
人工智能
数理经济学
数学
量子力学
机器学习
神经科学
政治
艺术
哲学
物理
文学类
政治学
法学
标识
DOI:10.1177/1088868313495594
摘要
Dual-system approaches to psychology explain the fundamental properties of human judgment, decision making, and behavior across diverse domains. Yet, the appropriate characterization of each system is a source of debate. For instance, a large body of research on moral psychology makes use of the contrast between “emotional” and “rational/cognitive” processes, yet even the chief proponents of this division recognize its shortcomings. Largely independently, research in the computational neurosciences has identified a broad division between two algorithms for learning and choice derived from formal models of reinforcement learning. One assigns value to actions intrinsically based on past experience, while another derives representations of value from an internally represented causal model of the world. This division between action- and outcome-based value representation provides an ideal framework for a dual-system theory in the moral domain.
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