Mixed-Initiative Level Design with RL Brush

08/06/2020
by   Omar Delarosa, et al.
7

This paper introduces RL Brush, a level-editing tool for tile-based games designed for mixed-initiative co-creation. The tool uses reinforcement-learning-based models to augment manual human level-design through the addition of AI-generated suggestions. Here, we apply RL Brush to designing levels for the classic puzzle game Sokoban. We put the tool online and tested it with 39 different sessions. The results show that users using the AI suggestions stay around longer and their created levels on average are more playable and more complex than without.

READ FULL TEXT

page 2

page 5

research
02/11/2020

Mech-Elites: Illuminating the Mechanic Space of GVGAI

This paper introduces a fully automatic method of mechanic illumination ...
research
08/02/2023

Lode Encoder: AI-constrained co-creativity

We present Lode Encoder, a gamified mixed-initiative level creation syst...
research
01/18/2019

Friend, Collaborator, Student, Manager: How Design of an AI-Driven Game Level Editor Affects Creators

Machine learning advances have afforded an increase in algorithms capabl...
research
08/03/2023

Lode Enhancer: Level Co-creation Through Scaling

We explore AI-powered upscaling as a design assistance tool in the conte...
research
03/05/2021

Deep Hedging, Generative Adversarial Networks, and Beyond

This paper introduces a potential application of deep learning and artif...
research
10/07/2021

The Impact of Visualizing Design Gradients for Human Designers

Mixed-initiative Procedural Content Generation (PCG) refers to tools or ...
research
11/20/2019

Integrating Automated Play in Level Co-Creation

In level co-creation an AI and human work together to create a video gam...

Please sign up or login with your details

Forgot password? Click here to reset