Aesthetic Bot: Interactively Evolving Game Maps on Twitter
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Abstract (arXiv)
This paper describes the implementation of the Aesthetic Bot, an automated Twitter account that posts images of small game maps that are either user-made or generated from an evolutionary system. The bot then prompts users to vote via a poll posted in the image's thread for the most aesthetically pleasing map. This creates a rating system that allows for direct interaction with the bot in a way that is integrated seamlessly into a user's regularly updated Twitter content feed. Upon conclusion of the each voting round, the bot learns from the distribution of votes for each map to emulate user preferences for design and visual aesthetic in order to generate maps that would win future vote pairings. We discuss the ongoing results and emerging behaviors that have occurred since the release of this system from both the bot's generation of game maps and the participating Twitter users.
Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 9 of its 28 references that are in the map. First posted on arXiv 9 Aug 2022.
Builds on
9 of 28 references.
References · 9
- 2018Evolving Mario Levels in the Latent Space of a Deep Convolutional Generative Adversarial Networkcited by 76
- 2021Learning Controllable Content Generatorscited by 40
- 2018Generative Design in Minecraft (GDMC), Settlement Generation Competitioncited by 22
- 2020Baba is Y'all: Collaborative Mixed-Initiative Level Designcited by 20
- 2019Tile Pattern KL-Divergence for Analysing and Evolving Game Levelscited by 16
- 2018Deep Interactive Evolutioncited by 13
- 2020Multi-Objective level generator generation with Marahelcited by 8
- 2022TropeTwist: Trope-based Narrative Structure Generationcited by 8
- 2021Procedural Content Generation using Behavior Trees (PCGBT)cited by 2
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Citing papers per year: 2023: 1; 2024: 1.
2 papers.