121 citations · 218 across the 8 of their papers we have counts for
11 papers
Language Model Crossover: Variation through Few-Shot Prompting
Elliot Meyerson, Mark J. Nelson, Herbie Bradley +4
This paper pursues the insight that language models naturally enable an intelligent variation operator similar in spirit to evolutionary crossover. In particular, language models o…
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…
Deep Surrogate Assisted MAP-Elites for Automated Hearthstone Deckbuilding
Yulun Zhang, Matthew C. Fontaine, Amy K. Hoover +1
We study the problem of efficiently generating high-quality and diverse content in games. Previous work on automated deckbuilding in Hearthstone shows that the quality diversity al…
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…
Covariance Matrix Adaptation for the Rapid Illumination of Behavior Space
Matthew C. Fontaine, Julian Togelius, Stefanos Nikolaidis +1
We focus on the challenge of finding a diverse collection of quality solutions on complex continuous domains. While quality diver-sity (QD) algorithms like Novelty Search with Loca…
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…
Mapping Hearthstone Deck Spaces through MAP-Elites with Sliding Boundaries
Matthew C. Fontaine, Scott Lee, L. B. Soros +3
Quality diversity (QD) algorithms such as MAP-Elites have emerged as a powerful alternative to traditional single-objective optimization methods. They were initially applied to evo…
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…