# TropeTwist: Trope-based Narrative Structure Generation

arXiv: https://arxiv.org/abs/2204.09672 · HTML: https://mlsanity.com/paper/2204.09672/

## Key facts

- Cited by 8 papers in the map (data through 14 Oct 2026).
- Builds on 15 of its 68 references that are in the map.
- First posted on arXiv 31 Mar 2022.

## Builds on (most cited first, 15 of 15)

- [Illuminating search spaces by mapping elites](https://mlsanity.com/paper/1504.04909/) (2015)
- [Obstacle Tower: A Generalization Challenge in Vision, Control, and Planning](https://mlsanity.com/paper/1902.01378/) (2019)
- [Controllable Neural Story Plot Generation via Reward Shaping](https://mlsanity.com/paper/1809.10736/) (2018)
- [Story Realization: Expanding Plot Events into Sentences](https://mlsanity.com/paper/1909.03480/) (2019)
- [Talakat: Bullet Hell Generation through Constrained Map-Elites](https://mlsanity.com/paper/1806.04718/) (2018)
- [Baba is Y'all: Collaborative Mixed-Initiative Level Design](https://mlsanity.com/paper/2003.14294/) (2020)
- [Empowering Quality Diversity in Dungeon Design with Interactive Constrained MAP-Elites](https://mlsanity.com/paper/1906.05175/) (2019)
- [Toward Automated Quest Generation in Text-Adventure Games](https://mlsanity.com/paper/1909.06283/) (2019)
- [Mech-Elites: Illuminating the Mechanic Space of GVGAI](https://mlsanity.com/paper/2002.04733/) (2020)
- [Interactive Constrained MAP-Elites: Analysis and Evaluation of the Expressiveness of the Feature Dimensions](https://mlsanity.com/paper/2003.03377/) (2020)
- [Dungeon and Platformer Level Blending and Generation using Conditional VAEs](https://mlsanity.com/paper/2106.12692/) (2021)
- [Fabula Entropy Indexing: Objective Measures of Story Coherence](https://mlsanity.com/paper/2104.07472/) (2021)
- [SuSketch: Surrogate Models of Gameplay as a Design Assistant](https://mlsanity.com/paper/2103.11726/) (2021)
- [Let CONAN tell you a story: Procedural quest generation](https://mlsanity.com/paper/1808.06217/) (2018)
- [Game Mechanic Alignment Theory and Discovery](https://mlsanity.com/paper/2102.10247/) (2021)

## Built on by (most cited first, 8 of 8)

- [Affective Game Computing: A Survey](https://mlsanity.com/paper/2309.14104/) (2023)
- [Story Designer: Towards a Mixed-Initiative Tool to Create Narrative Structures](https://mlsanity.com/paper/2210.09294/) (2022)
- [G-PCGRL: Procedural Graph Data Generation via Reinforcement Learning](https://mlsanity.com/paper/2407.10483/) (2024)
- [Aesthetic Bot: Interactively Evolving Game Maps on Twitter](https://mlsanity.com/paper/2208.05017/) (2022)
- [Multigenre AI-powered Story Composition](https://mlsanity.com/paper/2405.06685/) (2024)
- [The Quest for Content: A Survey of Search-Based Procedural Content Generation for Video Games](https://mlsanity.com/paper/2311.04710/) (2023)
- [Simulation-Driven Balancing of Competitive Game Levels with Reinforcement Learning](https://mlsanity.com/paper/2503.18748/) (2025)
- [The Garden of Forking Paths: Threading Narrative Archetype as a Semantic Signal Through Gameplay Planning](https://mlsanity.com/paper/2605.01245/) (2026)

## Abstract (arXiv)

Games are complex, multi-faceted systems that share common elements and underlying narratives, such as the conflict between a hero and a big bad enemy or pursuing a goal that requires overcoming challenges. However, identifying and describing these elements together is non-trivial as they might differ in certain properties and how players might encounter the narratives. Likewise, generating narratives also pose difficulties when encoding, interpreting, and evaluating them. To address this, we present TropeTwist, a trope-based system that can describe narrative structures in games in a more abstract and generic level, allowing the definition of games' narrative structures and their generation using interconnected tropes, called narrative graphs. To demonstrate the system, we represent the narrative structure of three different games. We use MAP-Elites to generate and evaluate novel quality-diverse narrative graphs encoded as graph grammars, using these three hand-made narrative structures as targets. Both hand-made and generated narrative graphs are evaluated based on their coherence and interestingness, which are improved through evolution.