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Found 10 papers, 4 papers with code
Procedural Content Generation via Knowledge Transformation (PCG-KT)
We introduce the concept of Procedural Content Generation via Knowledge Transformation (PCG-KT), a new lens and framework for characterizing PCG methods and approaches in which content generation is enabled by the process of knowledge transformation -- transforming knowledge derived from one domain in order to apply it in another.
Exploring Level Blending across Platformers via Paths and Affordances
Techniques for procedural content generation via machine learning (PCGML) have been shown to be useful for generating novel game content.
How to Tame Your Data: Data Augmentation for Dialog State Tracking
Dialog State Tracking (DST) is a problem space in which the effective vocabulary is practically limitless.
Automatic Mapping of NES Games with Mappy
Game maps are useful for human players, general-game-playing agents, and data-driven procedural content generation.
Mechanics Automatically Recognized via Interactive Observation: Jumping
Jumping has been an important mechanic since its introduction in Donkey Kong.
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.
Off The Beaten Lane: AI Challenges In MOBAs Beyond Player Control
MOBAs represent a huge segment of online gaming and are growing as both an eSport and a casual genre.
Procedural Content Generation via Machine Learning (PCGML)
This survey explores Procedural Content Generation via Machine Learning (PCGML), defined as the generation of game content using machine learning models trained on existing content.
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.
