no code implementations • 26 Apr 2016 • Jacob Schrum, Joel Lehman, Sebastian Risi
Indirect encodings can potentially answer this challenge.
no code implementations • 24 Mar 2017 • Alex C. Rollins, Jacob Schrum
Previous research using evolutionary computation in Multi-Agent Systems indicates that assigning fitness based on team vs.\ individual behavior has a strong impact on the ability of evolved teams of artificial agents to exhibit teamwork in challenging tasks.
3 code implementations • 2 May 2018 • Vanessa Volz, Jacob Schrum, Jialin Liu, Simon M. Lucas, Adam Smith, Sebastian Risi
This paper trains a GAN to generate levels for Super Mario Bros using a level from the Video Game Level Corpus.
no code implementations • 14 Jan 2020 • Jake Gutierrez, Jacob Schrum
Only the GAN approach creates an extensive supply of both layouts and rooms, where rooms span across the spectrum of those seen in the training set to new creations merging design principles from multiple rooms.
1 code implementation • 31 Mar 2020 • Jacob Schrum, Jake Gutierrez, Vanessa Volz, Jialin Liu, Simon Lucas, Sebastian Risi
A user study shows that both the evolution and latent space exploration features are appreciated, with a slight preference for direct exploration, but combining these features allows users to discover even better levels.
2 code implementations • 3 Apr 2020 • Jacob Schrum, Vanessa Volz, Sebastian Risi
In particular, GAN output does not scale to arbitrary dimensions, and there is no obvious way of combining multiple GAN outputs into a cohesive whole, which would be useful in many areas, such as the generation of video game levels.
1 code implementation • 19 Jan 2021 • Kirby Steckel, Jacob Schrum
Generative Adversarial Networks (GANs) are capable of generating convincing imitations of elements from a training set, but the distribution of elements in the training set affects to difficulty of properly training the GAN and the quality of the outputs it produces.
no code implementations • 30 Jan 2021 • Benjamin Capps, Jacob Schrum
Generative Adversarial Networks (GANs) can generate levels for a variety of games.
2 code implementations • 27 May 2021 • Jacob Schrum, Benjamin Capps, Kirby Steckel, Vanessa Volz, Sebastian Risi
However, collections of latent vectors can also be evolved directly, producing more chaotic levels.
1 code implementation • 1 Feb 2023 • Alejandro Medina, Melanie Richey, Mark Mueller, Jacob Schrum
Minecraft is a great testbed for human creativity that has inspired the design of various structures and even functioning machines, including flying machines.