… program), and are long (tens or hundreds of symbols). Additionally, matching rendered images
… images using Deep Reinforced Adversarial Learning. In this approach, an adversarially …

… training objective does not guarantee visual fidelity. To address these limitations, we propose
to use Reinforced Adversarial Learning (… enable a similar process for training and testing to …

… reinforced adversarial learning framework [8], where final goals are specified to the agent
via images … also draws inspiration from Visual Question Answering and Analysis-by-Synthesis: …

… Training generator maximization of the expected return which can be solved using
standard techniques from reinforcement learning. Use Advantage Actor Critic …

… We learn a model that uses program synthesis techniques to recover a graphics program
from that spec. These … We seek to synthesize graphics programs from their specs. …

… of interaction with a REPL, and use reinforcement learning techniques to train an agent to …
set of programs pp to a set of images. The policy then takes in the REPL state (a set of images)…

… To incorporate image editing software into a GAN, we propose a reinforcement learning
framework … (2018) proposed a reinforced adversarial learning method for synthesizing simple …

… images from which they compute a reward signal. Ellis et al. [8] use program synthesis to …
It uses the REINFORCE [37] algorithm to learn in an unsupervised manner, but runs into issues …

… adaptation, reinforcement learning and generative adversarial networks have … of using a
generating neural network for the synthesis of stylized images that can be used as input images …

… study natural images. SPIRAL [16], and its follow-up SPIRAL++ [30], both used reinforcement
learning … perspective plane program induction (P3I), a framework for synthesizing graphics …