97 citations · 198 across the 4 of their papers we have counts for
6 papers
Automatic Mapping of NES Games with Mappy
Joseph C. Osborn, Adam Summerville, Michael Mateas
Game maps are useful for human players, general-game-playing agents, and data-driven procedural content generation. These maps are generally made by hand-assembling manually-create…
CHARDA: Causal Hybrid Automata Recovery via Dynamic Analysis
Adam Summerville, Joseph Osborn, Michael Mateas
We propose and evaluate a new technique for learning hybrid automata automatically by observing the runtime behavior of a dynamical system. Working from a sequence of continuous st…
Automated Game Design Learning
Joseph C Osborn, Adam Summerville, Michael Mateas
While general game playing is an active field of research, the learning of game design has tended to be either a secondary goal of such research or it has been solely the domain of…
CFGs-2-NLU: Sequence-to-Sequence Learning for Mapping Utterances to Semantics and Pragmatics
Adam James Summerville, James Ryan, Michael Mateas +1
In this paper, we present a novel approach to natural language understanding that utilizes context-free grammars (CFGs) in conjunction with sequence-to-sequence (seq2seq) deep lear…
The VGLC: The Video Game Level Corpus
Adam James Summerville, Sam Snodgrass, Michael Mateas +1
Levels are a key component of many different video games, and a large body of work has been produced on how to procedurally generate game levels. Recently, Machine Learning techniq…
Super Mario as a String: Platformer Level Generation Via LSTMs
Adam Summerville, Michael Mateas
The procedural generation of video game levels has existed for at least 30 years, but only recently have machine learning approaches been used to generate levels without specifying…