# Exploring open-ended gameplay features with Micro RollerCoaster Tycoon

arXiv: https://arxiv.org/abs/2105.04342 · HTML: https://mlsanity.com/paper/2105.04342/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 9 of its 24 references that are in the map.
- First posted on arXiv 10 May 2021.

## Builds on (most cited first, 9 of 9)

- [Robots that can adapt like animals](https://mlsanity.com/paper/1407.3501/) (2014)
- [Quality and Diversity Optimization: A Unifying Modular Framework](https://mlsanity.com/paper/1708.09251/) (2017)
- [Autonomous skill discovery with Quality-Diversity and Unsupervised Descriptors](https://mlsanity.com/paper/1905.11874/) (2019)
- [Procedural Content Generation through Quality Diversity](https://mlsanity.com/paper/1907.04053/) (2019)
- [Talakat: Bullet Hell Generation through Constrained Map-Elites](https://mlsanity.com/paper/1806.04718/) (2018)
- [Empowering Quality Diversity in Dungeon Design with Interactive Constrained MAP-Elites](https://mlsanity.com/paper/1906.05175/) (2019)
- [Mech-Elites: Illuminating the Mechanic Space of GVGAI](https://mlsanity.com/paper/2002.04733/) (2020)
- [Using Fractal Neural Networks to Play SimCity 1 and Conway's Game of Life at Variable Scales](https://mlsanity.com/paper/2002.03896/) (2020)
- [Say "Sul Sul!" to SimSim, A Sims-Inspired Platform for Sandbox Game AI](https://mlsanity.com/paper/2008.11258/) (2020)

## Built on by (most cited first, 2 of 2)

- [Amorphous Fortress: Observing Emergent Behavior in Multi-Agent FSMs](https://mlsanity.com/paper/2306.13169/) (2023)
- [Quality Diversity in the Amorphous Fortress (QD-AF): Evolving for Complexity in 0-Player Games](https://mlsanity.com/paper/2312.02231/) (2023)

## Abstract (arXiv)

This paper introduces MicroRCT, a novel open source simulator inspired by the theme park sandbox game RollerCoaster Tycoon. The goal in MicroRCT is to place rides and shops in an amusement park to maximize profit earned from park guests. Thus, the challenges for game AI include both selecting high-earning attractions and placing them in locations that are convenient to guests. In this paper, the MAP-Elites algorithm is used to generate a diversity of park layouts, exploring two theoretical questions about evolutionary algorithms and game design: 1) Is there a benefit to starting from a minimal starting point for evolution and complexifying incrementally? and 2) What are the effects of resource limitations on creativity and optimization? Results indicate that building from scratch with no costs results in the widest diversity of high-performing designs.