This article introduces an experimental artwork that employs a reinforcement learning algorithm as core element for an interactive and aesthetic experience. The learning algorithm involves a simple navigation task for a single agent. The agent’s learning process is made perceivable to visitors by animating and visualizing a massive particle system on which the agent’s memory acts as force field. Through interaction, visitors can either facilitate or hamper the agent’s learning process. The goal of the artwork is to convey in a playful manner the increasingly intertwined coexistence between humans and artificially intelligent entities.

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General Conference
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© 2023 Massachusetts Institute of Technology Published under a Creative Commons Attribution 4.0 International (CC BY 4.0) license
2023
Massachusetts Institute of Technology
This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. For a full description of the license, please visit https://creativecommons.org/licenses/by/4.0/legalcode.
Issue Section:
General Conference