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Learning to Paint With Model-based Deep Reinforcement Learning
[article]
2019
arXiv
pre-print
We show how to teach machines to paint like human painters, who can use a small number of strokes to create fantastic paintings. By employing a neural renderer in model-based Deep Reinforcement Learning (DRL), our agents learn to determine the position and color of each stroke and make long-term plans to decompose texture-rich images into strokes. Experiments demonstrate that excellent visual effects can be achieved using hundreds of strokes. The training process does not require the experience
arXiv:1903.04411v3
fatcat:j5dvpxwanzc4vda3aue3j4p6t4