143 citations · 546 across the 35 of their papers we have counts for
10 papers · 1 filter
Bootstrapping Conditional GANs for Video Game Level Generation
Ruben Rodriguez Torrado, Ahmed Khalifa, Michael Cerny Green +3
Generative Adversarial Networks (GANs) have shown im-pressive results for image generation. However, GANs facechallenges in generating contents with certain types of con-straints,…
Automatic Critical Mechanic Discovery Using Playtraces in Video Games
Michael Cerny Green, Ahmed Khalifa, Gabriella A. B. Barros +2
We present a new method of automatic critical mechanic discovery for video games using a combination of game description parsing and playtrace information. This method is applied t…
Superstition in the Network: Deep Reinforcement Learning Plays Deceptive Games
Philip Bontrager, Ahmed Khalifa, Damien Anderson +3
Deep reinforcement learning has learned to play many games well, but failed on others. To better characterize the modes and reasons of failure of deep reinforcement learners, we te…
Procedural Content Generation through Quality Diversity
Daniele Gravina, Ahmed Khalifa, Antonios Liapis +2
Quality-diversity (QD) algorithms search for a set of good solutions which cover a space as defined by behavior metrics. This simultaneous focus on quality and diversity with expli…
General Video Game Rule Generation
Ahmed Khalifa, Michael Cerny Green, Diego Perez-Liebana +1
We introduce the General Video Game Rule Generation problem, and the eponymous software framework which will be used in a new track of the General Video Game AI (GVGAI) competition…
Two-step Constructive Approaches for Dungeon Generation
Michael Cerny Green, Ahmed Khalifa, Athoug Alsoughayer +3
This paper presents a two-step generative approach for creating dungeons in the rogue-like puzzle game MiniDungeons 2. Generation is split into two steps, initially producing the a…