121 citations · 251 across the 23 of their papers we have counts for
5 papers · 1 filter
Deep Surrogate Assisted Generation of Environments
Varun Bhatt, Bryon Tjanaka, Matthew C. Fontaine +1
Recent progress in reinforcement learning (RL) has started producing generally capable agents that can solve a distribution of complex environments. These agents are typically test…
Differentiable Quality Diversity
Matthew C. Fontaine, Stefanos Nikolaidis
Quality diversity (QD) is a growing branch of stochastic optimization research that studies the problem of generating an archive of solutions that maximize a given objective functi…
Video Game Level Repair via Mixed Integer Linear Programming
Hejia Zhang, Matthew C. Fontaine, Amy K. Hoover +3
Recent advancements in procedural content generation via machine learning enable the generation of video-game levels that are aesthetically similar to human-authored examples. Howe…
Illuminating Mario Scenes in the Latent Space of a Generative Adversarial Network
Matthew C. Fontaine, Ruilin Liu, Ahmed Khalifa +4
Generative adversarial networks (GANs) are quickly becoming a ubiquitous approach to procedurally generating video game levels. While GAN generated levels are stylistically similar…
Evolving the Hearthstone Meta
Fernando de Mesentier Silva, Rodrigo Canaan, Scott Lee +3
Balancing an ever growing strategic game of high complexity, such as Hearthstone is a complex task. The target of making strategies diverse and customizable results in a delicate i…