GameRule: a multi-agent architecture for game behavior specification

Abstract The specification of video-game behavior is commonly expressed through general-purpose scripting, coupling behavior definition to the components, callbacks, and APIs of a particular engine. This paper introduces GameRule , a multi-agent architecture for game behavior specification whose programming model is expressed through a domain-specific language (DSL) and realized by a reusable engine backend. Behavior is declared per actor as local when-do rules over a uniform property namespace covering the current actor, other actors, and the global game state. State access and transformation are expressed through a closed set of CRUD-based operations (Create, Read, Update, Delete), including higher-level actions whose engine-specific realization is delegated to the backend. Following the multi-agent system (MAS) paradigm, rules are declared locally to each actor but evaluated under a deterministic execution contract: a central scheduler traverses active actors in declaration order, actor evaluations are non-interleaved, and writes become immediately visible in execution order. The architecture is realized in Unity through a code generator that parses GameRule descriptors and produces C# scripts and configured game objects. Validation uses reimplementations of three games drawn from official Unity tutorials: John Lemon’s Haunted Jaunt , Survival Shooter , and Tanks . The three games use six conditions and fourteen actions without game-specific C# programming and show that the current model can represent and execute the gameplay mechanics and actor behaviors exercised by the tutorials in Unity. The evaluation also identifies recurring engine-specific responsibilities implemented once in the reusable backend, runtime cost and scaling limits, and behavior outside the model. Only the Unity backend has been implemented, so realization in other engines remains an architectural extension point rather than demonstrated portability.

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Publication Details

Journal
Multimedia Systems
Published
2026-09-06
DOI
https://doi.org/10.1007/s00530-026-02629-8
Primary Topic
Artificial Intelligence in Games
Type
article
Field-Weighted Citation Impact
0.00

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article

GameRule: a multi-agent architecture for game behavior specification

Miguel Chover, Carlos Marín-Lora, Nadia Montaña Miranda
Multimedia Systems
Artificial Intelligence in Games
article

GameRule: a multi-agent architecture for game behavior specification

Miguel Chover, Carlos Marín-Lora, Nadia Montaña Miranda
article en

Abstract

Abstract The specification of video-game behavior is commonly expressed through general-purpose scripting, coupling behavior definition to the components, callbacks, and APIs of a particular engine. This paper introduces GameRule , a multi-agent architecture for game behavior specification whose programming model is expressed through a domain-specific language (DSL) and realized by a reusable engine backend. Behavior is declared per actor as local when-do rules over a uniform property namespace covering the current actor, other actors, and the global game state. State access and transformation are expressed through a closed set of CRUD-based operations (Create, Read, Update, Delete), including higher-level actions whose engine-specific realization is delegated to the backend. Following the multi-agent system (MAS) paradigm, rules are declared locally to each actor but evaluated under a deterministic execution contract: a central scheduler traverses active actors in declaration order, actor evaluations are non-interleaved, and writes become immediately visible in execution order. The architecture is realized in Unity through a code generator that parses GameRule descriptors and produces C# scripts and configured game objects. Validation uses reimplementations of three games drawn from official Unity tutorials: John Lemon’s Haunted Jaunt , Survival Shooter , and Tanks . The three games use six conditions and fourteen actions without game-specific C# programming and show that the current model can represent and execute the gameplay mechanics and actor behaviors exercised by the tutorials in Unity. The evaluation also identifies recurring engine-specific responsibilities implemented once in the reusable backend, runtime cost and scaling limits, and behavior outside the model. Only the Unity backend has been implemented, so realization in other engines remains an architectural extension point rather than demonstrated portability.

Multimedia SystemsVol. 32(9)
Universitat Jaume I (ES), Universidad de Zaragoza (ES)
Universitat Jaume I, Agencia Estatal de Investigación
Peace, Justice and strong institutions
Openalex Percentile: Top 8%
Artificial Intelligence in Games
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