58 citations · 170 across the 17 of their papers we have counts for
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cs.AI2018
Evolving Mario Levels in the Latent Space of a Deep Convolutional Generative Adversarial Network
Vanessa Volz, Jacob Schrum, Jialin Liu +3
Generative Adversarial Networks (GANs) are a machine learning approach capable of generating novel example outputs across a space of provided training examples. Procedural Content…
cs.AI2018
Automated Curriculum Learning by Rewarding Temporally Rare Events
Niels Justesen, Sebastian Risi
Reward shaping allows reinforcement learning (RL) agents to accelerate learning by receiving additional reward signals. However, these signals can be difficult to design manually,…