Collaborative Research: Knowledge Transmission Through Iterated Learning

人类的许多知识不是从我们周围的物质世界学来的，而是从其他人那里学到的。例如，每一代新物理学家都不必重新发现牛顿力学定律；这些定律是从一个物理学家传给下一个物理学家的。同样的“迭代学习”也发生在语言、音乐和其他复杂的知识上，可以说，这些知识很难从头开始重新学习。尽管迭代学习在人类文化和社会中无处不在，但人们对知识从一个人传递给另一个人时的认知过程知之甚少。在国家科学基金会的支持下，卡里什博士和格里菲斯博士将通过测试和扩展将文化进化的数学与人类认知过程相统一的理论来研究这个问题。他们将进行一系列实验，旨在实验室环境中重现迭代学习的过程，并将通过开发计算模型来补充这些实验，这些计算模型旨在根据观察到的学习数据来测试理论预测。主要问题是，在传播过程中可能发生的相对较小的知识扰动是否会在多次迭代过程中累积起来产生较大的影响。这些实验的结果有望为我们提供一些对人类认知理论以及知识文化传播理论的重要和普遍的制约。

Much of human knowledge is not learned from the physical world around us, but from other people. For example, each new generation of physicists does not have to rediscover the laws of Newtonian mechanics; these laws are passed on from one physicist to the next. This same kind of "iterated learning" occurs for language, music, and other kinds of complex knowledge that are not easily relearned from scratch, so to speak. Despite the ubiquity of iterated learning in human culture and society, very little is known about the cognitive processes by which knowledge changes when it is transmitted from one person to the next. With support from the National Science Foundation, Dr. Kalish and Dr. Griffiths will investigate this issue by testing and extending theories that unify the mathematics of cultural evolution with the processes of human cognition. They will conduct a series of experiments that are designed to reproduce the processes of iterated learning in a laboratory environment, and the experiments will be complemented by the development of computational models designed to test the theoretical predictions against the observed learning data. The main issue is whether relatively small perturbations in knowledge that may occur in the act of transmission will or will not add up to have large effects over the course of many iterations. The results of these experiments promise to provide us with some important and general constraints on theories of human cognition, as well as theories of cultural transmission of knowledge.