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Viewing Adaptive Social Choice Through the Lens of Associative Learning

机译:通过联想学习镜头观看自适应社交选择

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Because humans live in a dynamic and evolving social world, modeling the factors that guide social behavior has remained a challenge for psychology. In contrast, much progress has been made on understanding some of the more basic elements of human behavior, such as associative learning and memory, which has been successfully modeled in other species. Here we argue that applying an associative learning approach to social behavior can offer valuable insights into the human moral experience. We propose that the basic principles of associative learning-conserved across a range of species-can, in many situations, help to explain seemingly complex human behaviors, including altruistic, cooperative, and selfish acts. We describe examples from the social decision-making literature using Pavlovian learning phenomena (e.g., extinction, cue competition, stimulus generalization) to detail how a history of positive or negative social outcomes influences cognitive and affective mechanisms that shape moral choice. Examining how we might understand social behaviors and their likely reliance on domain-general mechanisms can help to generate testable hypotheses to further understand how social value is learned, represented, and expressed behaviorally.
机译:因为人类生活在一个充满活力和不断发展的社会世界中,所以建立指导社会行为的因素仍为心理学挑战。相比之下,了解有很大进展,就是了解人类行为的一些基本要素,例如联想学习和记忆,这些内容已经成功地以其他物种建模。在这里,我们认为将联想学习方法应用于社会行为,可以为人造道德体验提供有价值的见解。我们建议在许多情况下,在各种类型的各种物种中,协会学习的基本原则有助于解释看似复杂的人类行为,包括利他主义,合作和自私行为。我们描述了使用Pavlovian学习现象(例如,灭绝,提示竞争,刺激普遍化)来详细描述社会决策文学的例子,以详细介绍积极或负面社会结果的历史如何影响形状的德尔选择的认知和情感机制。审查我们如何理解社会行为以及他们对领域一般机制的可能依赖可以帮助生成可测试的假设,以进一步了解如何学习社会价值,代表和表达行为。

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