CAREER: Connecting Human and Machine Learning through Probabilistic Models of Cognition

人类学习新概念的速度比计算机快得多，通常只需要几个例子，而计算机可能需要数百个例子。这种非凡的能力部分是由于对世界的丰富经验，导致对可能形成类别的物体种类有很强的先验知识。本研究项目通过开发人类类别学习的概率模型，将心理学数据与计算机科学和统计学的最新理论联系起来，弥合了人类和机器学习之间的差距。这些数学和计算模型被用来探索人们如何如此迅速地学习类别，捕捉先验知识对分类的影响，并建立一个可用于测试心理学理论和训练机器学习系统的人类概念目录。在每种情况下，研究结合了心理学和计算机科学中使用的思想，方法和数据来源，使用分层贝叶斯模型和马尔可夫链蒙特卡罗算法来模拟人类认知，实验室实验来测试这些模型，以及大型数据库作为指导模型预测的统计信息来源。该研究项目整合了一项教育计划，包括本科生和研究生的教学和指导，关于认知概率模型的教科书的开发，旨在增加计算机科学和心理学社区之间联系的教程和研讨会，以及通过讲座和网站进行推广。

People are able to learn new concepts much faster than computers, often requiring only a handful of examples where a computer might require hundreds. This remarkable ability is partly the consequence of extensive experience with the world, resulting in strong prior knowledge about the kinds of objects that are likely to form categories. This research project bridges the gap between human and machine learning by developing probabilistic models of human category learning, connecting psychological data with the latest theories from computer science and statistics. These mathematical and computational models are used to explore how people learn categories so quickly, to capture the effects of prior knowledge on categorization, and to build a catalogue of human concepts that can be used to test psychological theories and to train machine learning systems. In each case, the research combines the ideas, methods, and sources of data used in psychology and computer science, using hierarchical Bayesian models and Markov chain Monte Carlo algorithms to model human cognition, laboratory experiments to test these models, and large databases as a source of statistical information that guides model predictions. This research program is integrated with an educational plan that incorporates undergraduate and graduate teaching and mentoring, development of a textbook on probabilistic models of cognition, tutorials and workshops aimed at increasing contact between the computer science and psychology communities, and outreach through talks and a website.