Probabilistic Imitation Learning in Infants and Robots

该项目的总体目标是通过模仿学习，并赋予机器人以这种方式学习的能力。这个跨学科的项目有两个主要目标。首先是创建机器人的模仿学习模型，将人工智能和贝叶斯机器学习的技术与模仿的认知和心理研究的见解结合起来。该项目将使用这些模型来开发一种类人机器人，它可以通过观看人类执行特定任务来学习。第二个是确定类人机器人的哪些特征可以让人类婴幼儿模仿它。这将有助于阐明婴儿是否将意图归因于机器人的问题。PI将与同样来自华盛顿大学的认知心理学家安德鲁·梅尔佐夫博士合作。该项目将促进两个实验室的学生之间的合作，并为他们提供开展跨学科研究的培训。

The overall goal of this project is to study learning through imitation and endow robots with the ability to learn in this manner. This cross-disciplinary project has two major goals. The first is to create models for imitation learning in robots that combines techniques from Artificial Intelligence and Bayesian machine learning with insights from cognitive and psychological studies of imitation. The project will use these models to develop a humanoid robot that can learn by watching humans perform specific tasks. The second is to determine what characteristics of a humanoid robot can cause human infants and toddlers to imitate it. This will help shed light on the question of whether infants ascribe intentions to robots. The PI will collaborate with cognitive psychologist, Dr. Andrew Meltzoff also from the University of Washington. The project will foster collaboration between students from both of their labs and provide them with training in carrying out interdisciplinary research.