Regular Games -- an Automata-Based General Game Playing Language

2025-11-13

AI Summary

Existing General Game Playing (GGP) systems face dual bottlenecks in computational efficiency and game design expressiveness. To address these, this paper introduces *Regular Games*: the first GGP framework whose core language is finite automata. Leveraging a hierarchical language architecture, it automatically compiles high-level game descriptions into low-level rule automata, uniformly supporting both finite-horizon and imperfect-information games. Crucially, finite automata serve as the formal semantic foundation—enabling minimal rule representation and efficient forward-model generation. A complete toolchain—including an LSP-based editor, automaton visualizer, debugger, and benchmarking suite—is developed to enhance developer productivity and analytical capability. Experiments demonstrate that Regular Games achieves faster forward-model generation than state-of-the-art systems such as Regular Boardgames and Ludii. This work establishes a new GGP paradigm that unifies theoretical rigor with practical engineering utility.

Technology Category

• Humans and AI: Game Design — Procedural Content Generation & Storytelling
• Knowledge Representation and Reasoning: Automated Reasoning and Theorem Proving
• Cognitive Modeling & Cognitive Systems: Agent Architectures

Application Category

• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions
• Economics, Online Markets and Human Computation: Cost models of using LLMs in production systems
• Graph Algorithms and Modeling for the Web: Foundation models and LLMs for Web-related graphs

Abstract

We propose a new General Game Playing (GGP) system called Regular Games (RG). The main goal of RG is to be both computationally efficient and convenient for game design. The system consists of several languages. The core component is a low-level language that defines the rules by a finite automaton. It is minimal with only a few mechanisms, which makes it easy for automatic processing (by agents, analysis, optimization, etc.). The language is universal for the class of all finite turn-based games with imperfect information. Higher-level languages are introduced for game design (by humans or Procedural Content Generation), which are eventually translated to a low-level language. RG generates faster forward models than the current state of the art, beating other GGP systems (Regular Boardgames, Ludii) in terms of efficiency. Additionally, RG's ecosystem includes an editor with LSP, automaton visualization, benchmarking tools, and a debugger of game description transformations.

Problem

• Creating computationally efficient general game playing system for finite turn-based games
• Developing convenient game design languages for human and procedural content generation
• Generating faster forward models than existing GGP systems like Regular Boardgames

Innovation

• Finite automaton defines game rules efficiently
• High-level languages translate to low-level automation
• Faster forward models outperform existing GGP systems