LuminAI (formerly Viewpoints AI) was an installation that explored how to create a truly open-ended human-AI improvisational embodied interaction experience with minimal pre-authored content knowledge for the AI character.
LuminAI (formerly Viewpoints AI)
LuminAI (formerly Viewpoints AI) was an installation that explored how to create a truly open-ended human-AI improvisational embodied interaction experience with minimal pre-authored content knowledge for the AI character.
The system used interactive learning techniques, reasoning strategies from human improvisers, and the Viewpoints framework from theatre & dance were used to learn, procedurally represent, and reason about movement and improvise contemporary movement and dance performances with non-expert users.
Previously, researched, designed, and implemented case-based and imitation learning methods to teach the agent movement improvisation through observation and interaction, as well as procedural reasoning about improvisational response generation within the Soar cognitive architecture.
The research was a Field Experiment grant finalist, successfully completed a collaboration with the T Lang Dance Company (Atlanta) as a hybrid improvised-choreographed dance performance piece called Post, was selected to the ACCelerate Festival at the Smithsonian Institution National Museum of American History, completed numerous international (and domestic) invited and peer-reviewed installations, was the winner of the Neukom Institute Turing Test in Creative Arts 2017: DanceX Prize, and produced six peer-reviewed publications.
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