Drawcto Co-Creative AI

Non-representational art--such as works by Wassily Kandinsky, Joan Mitchell, Willem de Kooning, etc.--showcases diverse artistic expressions and challenges viewers with its interpretive open-endedness and lack of a clear mapping to our everyday reality. Human cognition and perception nonetheless aid us in making sense of, reasoning about, and discussing the perceptual features prevalent in such non-representational art. While there have been various Computational Creative systems capable of generating representational artwork, only a few existing Computational (Co)Creative systems for visual arts can produce non-representational art. Inspired by this, we propose a new drawing application Drawcto a multi-agent AI that incorporates elements of the human visual perception theory capable of co-creating non-representational art with a human collaborator on the web.

Project Name
Faculty Lead(s)
Jason Freeman, Duri Long
Student Name(s)
Manoj Deshpande, Arpit Mathur, Bhavika Devnani, Laney Light, Luowen Qiao, Tianbai Jia
Main Contact
Brian Magerko
Lab Name
Expressive Machinery Lab (formerly ADAM Lab)
Video Title
Drawcto Co-Creative AI
Video URL
https://www.youtube.com/watch?v=-_YdkMzr-oA