Events and Machine Learning

In exploring some possible conditions for event segmentation, the articles in this spe-cial issue invite discussion on several important high-level questions. This commentary focuses on the two articles (Baldwin & Kosie, 2019; Shin & DuBrow, 2019), which give accounts of how cognitive agents might segment event boundaries. These papers highlight the role of organizing structure, especially hierarchy and abstraction, in information pro-cessing. Our own research engages with these ideas in the context of creating machinelearning (ML) agents that make sensible decisions in complicated environments, and we see a great deal of value in fields outside of computer science as we converge on someof the same questions