Applying machine learning to a robotics problem typically requires substantial human oversight to design the learning system, tune the parameters, define the task, determine the input and output representations and create the training data set. In contrast, biological organisms are able to learn autonomously from unlabeled data in an open-ended fashion. Developmental robotics is an emerging field that strives to build better robots by applying insights from biological developmental processes. In this talk, Lisa Meeden of Swarthmore College will review several recent approaches from developmental robotics that use prediction to generate teaching signals. This results in a task-independent kind of learning in which the robot focuses on novel stimuli.
The talk, part of the CSEE Colloquium, will be Tuesday, March 10, noon-1 p.m., in the Information Technology and Engineering building, Room 325B. Lunch will be provided at 11:30 a.m. for those who would like to meet Meeden before the talk. The host is Associate Professor of Computer Science and Electrical EngineeringMarie DesJardins. For more information, e-mail mariedj@cs.umbc.edu.
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