Search Results for author: Adam Summerville

Found 9 papers, 4 papers with code

Exploring Level Blending across Platformers via Paths and Affordances

no code implementations22 Aug 2020 Anurag Sarkar, Adam Summerville, Sam Snodgrass, Gerard Bentley, Joseph Osborn

Techniques for procedural content generation via machine learning (PCGML) have been shown to be useful for generating novel game content.

Automatic Mapping of NES Games with Mappy

1 code implementation12 Jul 2017 Joseph C. Osborn, Adam Summerville, Michael Mateas

Game maps are useful for human players, general-game-playing agents, and data-driven procedural content generation.

CHARDA: Causal Hybrid Automata Recovery via Dynamic Analysis

1 code implementation11 Jul 2017 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.

Model Selection

Automated Game Design Learning

1 code implementation11 Jul 2017 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 humans.

Off The Beaten Lane: AI Challenges In MOBAs Beyond Player Control

no code implementations9 Jun 2017 Michael Cook, Adam Summerville, Simon Colton

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)

no code implementations2 Feb 2017 Adam Summerville, Sam Snodgrass, Matthew Guzdial, Christoffer Holmgård, Amy K. Hoover, Aaron Isaksen, Andy Nealen, Julian Togelius

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.

Card Games Style Transfer

Super Mario as a String: Platformer Level Generation Via LSTMs

no code implementations2 Mar 2016 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 the rules for generation.

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