28 citations · 37 across the 3 of their papers we have counts for
6 papers
Finding Game Levels with the Right Difficulty in a Few Trials through Intelligent Trial-and-Error
Miguel González-Duque, Rasmus Berg Palm, David Ha +1
Methods for dynamic difficulty adjustment allow games to be tailored to particular players to maximize their engagement. However, current methods often only modify a limited set of…
Scones: Towards Conversational Authoring of Sketches
Forrest Huang, Eldon Schoop, David Ha +1
Iteratively refining and critiquing sketches are crucial steps to developing effective designs. We introduce Scones, a mixed-initiative, machine-learning-driven system that enables…
Neuroevolution of Self-Interpretable Agents
Yujin Tang, Duong Nguyen, David Ha
Inattentional blindness is the psychological phenomenon that causes one to miss things in plain sight. It is a consequence of the selective attention in perception that lets us rem…
SketchTransfer: A Challenging New Task for Exploring Detail-Invariance and the Abstractions Learned by Deep Networks
Alex Lamb, Sherjil Ozair, Vikas Verma +1
Deep networks have achieved excellent results in perceptual tasks, yet their ability to generalize to variations not seen during training has come under increasing scrutiny. In thi…
Learning to Predict Without Looking Ahead: World Models Without Forward Prediction
C. Daniel Freeman, Luke Metz, David Ha
Much of model-based reinforcement learning involves learning a model of an agent's world, and training an agent to leverage this model to perform a task more efficiently. While the…
Deep Learning for Classical Japanese Literature
Tarin Clanuwat, Mikel Bober-Irizar, Asanobu Kitamoto +3
Much of machine learning research focuses on producing models which perform well on benchmark tasks, in turn improving our understanding of the challenges associated with those tas…