activity
20172026
most citedDeep Learning for Procedural Content Generation

143 citations · 546 across the 35 of their papers we have counts for

collaborators
Showing 2020 · cs.AIShow all

5 papers · 2 filters

cs.AI2020★ 143 cited

Deep Learning for Procedural Content Generation

Jialin Liu, Sam Snodgrass, Ahmed Khalifa +3

Procedural content generation in video games has a long history. Existing procedural content generation methods, such as search-based, solver-based, rule-based and grammar-based me…

cs.AI2020

Mixed-Initiative Level Design with RL Brush

Omar Delarosa, Hang Dong, Mindy Ruan +2

This paper introduces RL Brush, a level-editing tool for tile-based games designed for mixed-initiative co-creation. The tool uses reinforcement-learning-based models to augment ma…

cs.AI2020★ 8 cited

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…

cs.AI2020

Mario Level Generation From Mechanics Using Scene Stitching

Michael Cerny Green, Luvneesh Mugrai, Ahmed Khalifa +1

This paper presents a level generation method for Super Mario by stitching together pre-generated "scenes" that contain specific mechanics, using mechanic-sequences from agent play…

cs.AI2020

Mech-Elites: Illuminating the Mechanic Space of GVGAI

M Charity, Michael Cerny Green, Ahmed Khalifa +1

This paper introduces a fully automatic method of mechanic illumination for general video game level generation. Using the Constrained MAP-Elites algorithm and the GVG-AI framework…