  This paper proposes a framework for computational modeling of artistic
painting algorithms, inspired by human creative practices. Based on examples
from expert artists and from the author's own experience, the paper argues that
creative processes often involve two important components: vague, high-level
goals (e.g., "make a good painting"), and exploratory processes for discovering
new ideas. This paper then sketches out possible computational mechanisms for
imitating those elements of the painting process, including underspecified loss
functions and iterative painting procedures with explicit task decompositions.
