A social reinforcement learning agent
Proceedings of the fifth international conference on Autonomous agents
Reinforcement Learning in the Multi-Robot Domain
Autonomous Robots
Reinforcement learning: a survey
Journal of Artificial Intelligence Research
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In Socially Guided Machine Learning we explore the ways in which machine learning can more fully take advantage of natural human interaction. In this work we are studying the role real-time human interaction plays in training assistive robots to perform new tasks. We describe an experimental platform, Sophie's World, and present descriptive analysis of human teaching behavior found in a user study. We report three important observations of how people administer reward and punishment to teach a simulated robot a new task through Reinforcement Learning. People adjust their behavior as they develop a model of the learner, they use the reward channel for guidance as well as feedback, and they may also use it as a motivational channel.