8 citations · 11 across the 5 of their papers we have counts for
5 papers
Representing and Generating Levels Over Time through Playtrace Reconstructive Partitioning
Emily Halina, Matthew Guzdial
Video games are a dynamic medium experienced over time. While there are many Procedural Content Generation (PCG) approaches for generating video game levels, they often use represe…
Tree-Based Reconstructive Partitioning: A Novel Low-Data Level Generation Approach
Emily Halina, Matthew Guzdial
Procedural Content Generation (PCG) is the algorithmic generation of content, often applied to games. PCG and PCG via Machine Learning (PCGML) have appeared in published games. How…
Diversity-based Deep Reinforcement Learning Towards Multidimensional Difficulty for Fighting Game AI
Emily Halina, Matthew Guzdial
In fighting games, individual players of the same skill level often exhibit distinct strategies from one another through their gameplay. Despite this, the majority of AI agents for…
Threshold Designer Adaptation: Improved Adaptation for Designers in Co-creative Systems
Emily Halina, Matthew Guzdial
To best assist human designers with different styles, Machine Learning (ML) systems need to be able to adapt to them. However, there has been relatively little prior work on how an…
TaikoNation: Patterning-focused Chart Generation for Rhythm Action Games
Emily Halina, Matthew Guzdial
Generating rhythm game charts from songs via machine learning has been a problem of increasing interest in recent years. However, all existing systems struggle to replicate human-l…