mlsanityData to 14 Oct 2026

Game-Creation-Agents: Autonomous Game Production

arXiv 2610.16776 ↗First posted 12 Oct 2026cs.AI cs.MAcited by 0

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Abstract (arXiv)

Game-Creation-Agents (GCA) turns a natural-language request into a runnable Phaser 4 browser game. The pipeline first builds a multimodal game design document that couples mechanics and scene contracts to grounded visual references. It then projects that document into a runtime scaffold, machine-readable contracts, and deterministic tests. Eight specialized agents next carry out production: scenes are implemented serially, assets are produced in parallel, and one reduced manifest joins the two branches into a single build. Build-linked real-UI checks and a code-blind critic then verify that build and decide whether the game may ship. Each blocker returns to the agent that owns the affected artifact for a bounded repair, and the game is released once all the gates pass. We evaluate finished games separately, through their rendered interfaces alone, over prompt-matched tasks run under a common protocol. GCA achieves stronger requirement satisfaction, core mechanics, content depth, and functional visuals than a comparable open pipeline. In a side-by-side human study, raters also score GCA's games higher on every dimension and prefer them overall.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 30 of its 60 references that are in the map. First posted on arXiv 12 Oct 2026.

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30 of 60 references.

References · 30

  1. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,863
  2. 2022ReAct: Synergizing Reasoning and Acting in Language Modelscited by 8,695
  3. 2023Judging LLM-as-a-Judge with MT-Bench and Chatbot Arenacited by 8,626
  4. 2021Evaluating Large Language Models Trained on Codecited by 8,320
  5. 2023Reflexion: Language Agents with Verbal Reinforcement Learningcited by 4,276
  6. 2021Program Synthesis with Large Language Modelscited by 3,637
  7. 2023Self-Refine: Iterative Refinement with Self-Feedbackcited by 3,442
  8. 2023SWE-bench: Can Language Models Resolve Real-World GitHub Issues?cited by 3,373
  9. 2023Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasetscited by 2,581
  10. 2023Voyager: An Open-Ended Embodied Agent with Large Language Modelscited by 2,191
  11. 2023WebArena: A Realistic Web Environment for Building Autonomous Agentscited by 2,006
  12. 2023AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversationcited by 1,988
18 more
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  3. 2023ChatDev: Communicative Agents for Software Developmentcited by 919
  4. 2023CRITIC: Large Language Models Can Self-Correct with Tool-Interactive Critiquingcited by 783
  5. 2024SeeClick: Harnessing GUI Grounding for Advanced Visual GUI Agentscited by 567
  6. 2024GPT-4V(ision) is a Generalist Web Agent, if Groundedcited by 563
  7. 2024WebVoyager: Building an End-to-End Web Agent with Large Multimodal Modelscited by 438
  8. 2025Seedance 1.0: Exploring the Boundaries of Video Generation Modelscited by 259
  9. 2023VIEScore: Towards Explainable Metrics for Conditional Image Synthesis Evaluationcited by 201
  10. 2017Procedural Content Generation via Machine Learning (PCGML)cited by 137
  11. 2023MarioGPT: Open-Ended Text2Level Generation through Large Language Modelscited by 64
  12. 2023GameGPT: Multi-agent Collaborative Framework for Game Developmentcited by 43
  13. 2025VideoGameBench: Can Vision-Language Models complete popular video games?cited by 36
  14. 2026GameDevBench: Evaluating Agentic Capabilities Through Game Developmentcited by 28
  15. 2026GameCraft-Bench: Can Agents Build Playable Games End-to-End in a Real Game Engine?cited by 22
  16. 2026OpenGame: Open Agentic Coding for Gamescited by 18
  17. 2025Leveraging LLM Agents for Automated Video Game Testingcited by 5
  18. 2026GBQA: A Game Benchmark for Evaluating LLMs as Quality Assurance Engineerscited by 5

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