Online

Beaulieu, Shawn Lawrence

Complex Systems and Data Science

2023

Ph. D.

Devices which blur the distinction between the living and the inanimate are being reported with heightened frequency. But what forms of organization, and what modes of internal change and worldly interaction, are required for truly lifelike devices, rather than ones which abstractly mimic life in simulation? This thesis presents results from two publications which attempt to mitigate a problem known to limit the performance of artificial neural networks, called "catastrophic forgetting," and a third paper which tries to articulate a vision for the construction of more lifelike devices-whose form, function, and putative environment are not conclusively specified prior to their deployment, but result from their interaction with a world alive to their own making. The object of this work is thus to improve both the technical proficiency of existing devices and the orientation of that proficiency according to the material interests of every day users.