OpenAlex ·

Showing versus Doing: Teaching by Demonstration

Mark K. Ho, Michael L. Littman, James MacGlashan, Fiery Andrews Cushman and Joseph L. Austerweil

Published
Source
OpenAlex
Published in
arXiv (Cornell University)
DOI
10.48550/arxiv.2610.14004
Original
Read it at the publisher
Topics
Artificial Intelligence

Abstract

People often learn from others' demonstrations, and inverse reinforcement learning (IRL) techniques have realized this capacity in machines. In contrast, teaching by demonstration has been less well studied computationally. Here, we develop a Bayesian model for teaching by demonstration. Stark differences arise when demonstrators are intentionally teaching (i.e. showing) a task versus simply performing (i.e. doing) a task. In two experiments, we show that human participants modify their teaching behavior consistent with the predictions of our model. Further, we show that even standard IRL algorithms benefit when learning from showing versus doing.

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