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Academic Lectures / Courses
Genuine Helpers: Enabling natural language capabilities for interactive robots
Department / Organization: Computer Science
Learn how intelligent robots can communicate through natural language in realistic human-robot interaction scenarios, in which knowledge is uncertain, incomplete, and decentralized.
Genuine Helpers: Enabling natural language capabilities for interactive robots
Presented by: Computer Science Faculty Candidate Tom Williams
My research investigates how intelligent robots can communicate through natural language in realistic human-robot interaction scenarios, in which knowledge is uncertain, incomplete, and decentralized. To do so, I draw on techniques and concepts from artificial intelligence, psychology, linguistics, and philosophy, and engage in both algorithm development and empirical experimentation. In my talk, I will present a set of cognitively inspired algorithms I have developed to allow robots to better identify the entities (e.g., objects, people, and locations) referenced in natural language by their human conversational partners, and to better infer those conversational partners’ intentions, in uncertain and open worlds. I will then discuss how these algorithms have been implemented on a robotic wheelchair in order to significantly extend the state of the art of natural language enabled robot wheelchairs.
Tom Williams is a PhD candidate in the joint Computer Science and Cognitive Science program at Tufts University, where he teaches Artificial Intelligence. Tom’s research focuses on enabling and understanding natural language based human-robot interaction, especially as applied to assistive and search-and-rescue robotics, and has been published in top artificial intelligence, robotics, and cognitive science venues.