121 citations · 218 across the 8 of their papers we have counts for
7 papers · 1 filter
Watts: Infrastructure for Open-Ended Learning
Aaron Dharna, Charlie Summers, Rohin Dasari +2
This paper proposes a framework called Watts for implementing, comparing, and recombining open-ended learning (OEL) algorithms. Motivated by modularity and algorithmic flexibility,…
Transfer Dynamics in Emergent Evolutionary Curricula
Aaron Dharna, Amy K Hoover, Julian Togelius +1
PINSKY is a system for open-ended learning through neuroevolution in game-based domains. It builds on the Paired Open-Ended Trailblazer (POET) system, which originally explored lea…
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…
The Many AI Challenges of Hearthstone
Amy K. Hoover, Julian Togelius, Scott Lee +1
Games have benchmarked AI methods since the inception of the field, with classic board games such as Chess and Go recently leaving room for video games with related yet different s…
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…
Procedural Content Generation via Machine Learning (PCGML)
Adam Summerville, Sam Snodgrass, Matthew Guzdial +5
This survey explores Procedural Content Generation via Machine Learning (PCGML), defined as the generation of game content using machine learning models trained on existing content…