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Found 6 papers, 4 papers with code
Automatic Mapping of NES Games with Mappy
Game maps are useful for human players, general-game-playing agents, and data-driven procedural content generation.
Automated Game Design Learning
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 humans.
CHARDA: Causal Hybrid Automata Recovery via Dynamic Analysis
We propose and evaluate a new technique for learning hybrid automata automatically by observing the runtime behavior of a dynamical system.
CFGs-2-NLU: Sequence-to-Sequence Learning for Mapping Utterances to Semantics and Pragmatics
Because we already annotated the symbols in this grammar for the semantic and pragmatic considerations that our game's dialogue manager operates over, we can use the grammatical trace associated with any surface utterance to infer such information.
The VGLC: The Video Game Level Corpus
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.
Super Mario as a String: Platformer Level Generation Via LSTMs
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 the rules for generation.
