mlsanityData to 14 Oct 2026

Procedural Content Generation in Games: A Survey with Insights on Emerging LLM Integration

arXiv 2410.15644 ↗First posted 21 Oct 2024cs.AIcited by 22

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Abstract (arXiv)

Procedural Content Generation (PCG) is defined as the automatic creation of game content using algorithms. PCG has a long history in both the game industry and the academic world. It can increase player engagement and ease the work of game designers. While recent advances in deep learning approaches in PCG have enabled researchers and practitioners to create more sophisticated content, it is the arrival of Large Language Models (LLMs) that truly disrupted the trajectory of PCG advancement. This survey explores the differences between various algorithms used for PCG, including search-based methods, machine learning-based methods, other frequently used methods (e.g., noise functions), and the newcomer, LLMs. We also provide a detailed discussion on combined methods. Furthermore, we compare these methods based on the type of content they generate and the publication dates of their respective papers. Finally, we identify gaps in the existing academic work and suggest possible directions for future research.

Key facts. Cited by 22 papers in the map (data through 14 Oct 2026). Builds on 21 of its 92 references that are in the map. First posted on arXiv 21 Oct 2024.

Builds on

21 of 92 references.

References · 21

  1. 2017Attention Is All You Needcited by 60,361
  2. 2014Deep Learning in Neural Networks: An Overviewcited by 770
  3. 2015DRAW: A Recurrent Neural Network For Image Generationcited by 191
  4. 2021Monte Carlo Tree Search: A Review of Recent Modifications and Applicationscited by 161
  5. 2017Procedural Content Generation via Machine Learning (PCGML)cited by 137
  6. 2018Evolving Mario Levels in the Latent Space of a Deep Convolutional Generative Adversarial Networkcited by 76
  7. 2020Deep Learning for Procedural Content Generationcited by 73
  8. 2019Increasing Generality in Machine Learning through Procedural Content Generationcited by 59
  9. 2016Super Mario as a String: Platformer Level Generation Via LSTMscited by 40
  10. 2020Bringing Stories Alive: Generating Interactive Fiction Worldscited by 28
  11. 2020CPPN2GAN: Combining Compositional Pattern Producing Networks and GANs for Large-scale Pattern Generationcited by 19
  12. 2020Exploring Level Blending across Platformers via Paths and Affordancescited by 14
9 more
  1. 2023The Five-Dollar Model: Generating Game Maps and Sprites from Sentence Embeddingscited by 14
  2. 2020Multi-Domain Level Generation and Blending with Sketches via Example-Driven BSP and Variational Autoencoderscited by 11
  3. 202110 Years of the PCG workshop: Past and Future Trendscited by 6
  4. 2023The Ethics of AI in Gamescited by 6
  5. 2019Evaluation of a Recommender System for Assisting Novice Game Designerscited by 5
  6. 2020A quantum procedure for map generationcited by 4
  7. 2023Procedurally generating rules to adapt difficulty for narrative puzzle gamescited by 1
  8. 2023Lode Enhancer: Level Co-creation Through Scalingcited by 1
  9. 2023PCGPT: Procedural Content Generation via Transformerscited by 1

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 10; 2026: 12.

22 papers.

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  1. 2025WorldGen: From Text to Traversable and Interactive 3D Worldscited by 19
  2. 2026AutoUE: Automated Generation of 3D Games in Unreal Engine via Multi-Agent Systemscited by 9
  3. 2025TraceDet: Hallucination Detection from the Decoding Trace of Diffusion Large Language Modelscited by 8
  4. 2026JAMER: Project-Level Code Framework Dataset and Benchmark on Professional Game Enginescited by 6
  5. 2026Imagine a City: CityGenAgent for Procedural 3D City Generationcited by 5
  6. 2025Word2Minecraft: Generating 3D Game Levels through Large Language Modelscited by 3
  7. 2026Generative Ontology: When Structured Knowledge Learns to Createcited by 2
  8. 2025Symbolically Scaffolded Play: Designing Role-Sensitive Prompts for Generative NPC Dialoguecited by 1
  9. 2026From World-Gen to Quest-Line: A Dependency-Driven Prompt Pipeline for Coherent RPG Generationcited by 1
  10. 2026MAGIC: Transition-Aware Generation of Navigable Multi-Scene Game Worlds with Large Language Modelscited by 1
  11. 2025Hybrid Voting-Based Task Assignment in Role-Playing Gamescited by 0
  12. 2025State-Inference-Based Prompting for Natural Language Trading with Game NPCscited by 0
10 more
  1. 2025From Unstable to Playable: Stabilizing Angry Birds Levels via Object Segmentationcited by 0
  2. 2025Aligning Large Language Models with Procedural Rules: An Autoregressive State-Tracking Prompting for In-Game Tradingcited by 0
  3. 2025SEA-SafeguardBench: Evaluating AI Safety in SEA Languages and Culturescited by 0
  4. 2025Zero-shot 3D Map Generation with LLM Agents: A Dual-Agent Architecture for Procedural Content Generationcited by 0
  5. 2026RPA-Check: A Multi-Stage Automated Framework for Evaluating Dynamic LLM-based Role-Playing Agentscited by 0
  6. 2026From LLM-Driven Trading Card Generation to Procedural Relatedness: A Pok'emon Case Studycited by 0
  7. 2026VoxScene: Anchor-Conditioned Voxel Diffusion for Indoor Scene Arrangementcited by 0
  8. 2026An Exploration of Collision-based Enemy Morphology Generationcited by 0
  9. 2026AI Native Games: A Survey and Roadmapcited by 0
  10. 2026Optimal Stopping of Self-Refining Foundation Modelscited by 0