■ Optimization

Collaboration with, Maor Rosenberg (curiosity lab Tel Aviv University), Guy Amichay, Max Plank Institute, and the e-David team, (University of Konstanz)

Gallery, 301 Chung-Ang University Seoul, South Korea, 2017

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Saving, translating and repeating information in the painting process are features that computer- and robotic-based painting offers. These are used in my work to redefine, challenge and examine the structures and systems used in the process of making a painting by translating and assimilating logic from different disciplines into artistic expression. lately, I began investigating various methods for the transformation of information using the trajectories of organisms as a base to generate not only brushstrokes but even the entire architectonical structure of a painting.

The simple geometric form of a red rectangular creates a focal point for the viewer gaze, defining the space of action in which the architectural structure of the painting occurs.  The structure in this work was innately built using reinforcement learning algorithm, seeking for the optimal way to paint a red rectangular, raising the question--optimal in what way?

The finished work contains a selection of 8 trajectory paintings. The paintings are a repetition of the task to paint a red rectangular according to pre-giving parameters, however, they are not a repetition of the execution itself, rather of different approaches: paintings done by the e-David robot using reinforcement learning algorithm, trajectory of a fish movement which was following a VR red dot that operated according  to the reinforcement learning algorithm of making a red rectangular and manually painted red rectangular executed by me, while following predefined parameters (action score) aligning with the algorithm given to the robot and the fish.

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