CreativeGame:Toward Mechanic-Aware Creative Game Generation
Summary
CreativeGame is a multi-agent system that iteratively generates HTML5 games by explicitly planning, tracking, and evolving game mechanics across versions using programmatic rewards and lineage memory.
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Paper page - CreativeGame:Toward Mechanic-Aware Creative Game Generation
Source: https://huggingface.co/papers/2604.19926
Abstract
A multi-agent system for iterative HTML5 game generation that uses programmatic rewards, lineage memory, runtime validation, and mechanic-guided planning to enable interpretable version-to-version evolution.
Large language modelscan generate plausible game code, but turning this capability into iterative creative improvement remains difficult. In practice, single-shot generation often produces brittle runtime behavior, weak accumulation of experience across versions, and creativity scores that are too subjective to serve as reliable optimization signals. A further limitation is that mechanics are frequently treated only as post-hoc descriptions, rather than as explicit objects that can be planned, tracked, preserved, and evaluated during generation. This report presents CreativeGame, amulti-agent systemfor iterativeHTML5 game generationthat addresses these issues through four coupled ideas: aproxy rewardcentered onprogrammatic signalsrather than pure LLM judgment;lineage-scoped memoryfor cross-version experience accumulation;runtime validationintegrated into both repair and reward; and amechanic-guided planningloop in which retrieved mechanic knowledge is converted into an explicit mechanic plan before code generation begins. The goal is not merely to produce a playable artifact in one step, but to support interpretableversion-to-version evolution. The current system contains 71 stored lineages, 88 saved nodes, and a 774-entry global mechanic archive, implemented in 6{,}181 lines of Python together with inspection and visualization tooling. The system is therefore substantial enough to support architectural analysis, reward inspection, and real lineage-level case studies rather than only prompt-level demos. A real 4-generation lineage shows that mechanic-level innovation can emerge in later versions and can be inspected directly through version-to-version records. The central contribution is therefore not only game generation, but a concrete pipeline for observing progressive evolution through explicit mechanic change.
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