6 citations · 8 across the 3 of their papers we have counts for
7 papers
Making CNNs for Video Parsing Accessible
Zijin Luo, Matthew Guzdial, Mark Riedl
The ability to extract sequences of game events for high-resolution e-sport games has traditionally required access to the game's engine. This serves as a barrier to groups who don…
Guiding Reinforcement Learning Exploration Using Natural Language
Brent Harrison, Upol Ehsan, Mark O. Riedl
In this work we present a technique to use natural language to help reinforcement learning generalize to unseen environments. This technique uses neural machine translation, specif…
A Framework for Exploring and Evaluating Mechanics in Human Computation Games
Kristin Siu, Alexander Zook, Mark O. Riedl
Human computation games (HCGs) are a crowdsourcing approach to solving computationally-intractable tasks using games. In this paper, we describe the need for generalizable HCG desi…
Evaluating Singleplayer and Multiplayer in Human Computation Games
Kristin Siu, Matthew Guzdial, Mark O. Riedl
Human computation games (HCGs) can provide novel solutions to intractable computational problems, help enable scientific breakthroughs, and provide datasets for artificial intellig…
Learning to Blend Computer Game Levels
Matthew Guzdial, Mark Riedl
We present an approach to generate novel computer game levels that blend different game concepts in an unsupervised fashion. Our primary contribution is an analogical reasoning pro…
Toward Game Level Generation from Gameplay Videos
Matthew Guzdial, Mark Riedl
Algorithms that generate computer game content require game design knowledge. We present an approach to automatically learn game design knowledge for level design from gameplay vid…