Training Machines for Uncertain Real-World Situations
MIT News
Adam Zewe, May 31, 2023
An algorithm developed by researchers at the Massachusetts Institute of Technology (MIT) and Technion—Israel Institute of Technology can determine automatically and independently whether and when imitation learning or reinforcement learning is more effective for training a "student" machine. The algorithm is adaptive, allowing the machine to move between both types of learning throughout the training process based on which would achieve better, faster results. MIT's Idan Shenfeld said, "This combination of learning by trial-and-error and following a teacher is very powerful. It gives our algorithm the ability to solve very difficult tasks that cannot be solved by using either technique individually."
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