Aesthetic Bot: Interactively Evolving Game Maps on Twitter

TL;DR

The paper presents Aesthetic Bot, an interactive Twitter system that evolves game maps based on user votes, learning aesthetic preferences to generate increasingly appealing maps over time.

Contribution

It introduces a novel interactive platform combining social voting with evolutionary map generation to adapt and improve aesthetics based on user feedback.

Findings

The bot successfully learns user aesthetic preferences.

Participating users influence the evolution of map designs.

Emerging behaviors indicate evolving aesthetic trends.

Abstract

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.