Procedural Content Generation for GDL Descriptions of Simplified Boardgames

TL;DR

This paper introduces a method for procedurally generating simplified boardgames and translating them into GDL code, aiming to create diverse, balanced, and human-readable chess-like games for evaluating General Game Playing agents.

Contribution

It presents an adaptive evolutionary algorithm for generating playable, balanced, and human-readable simplified boardgames and translating them into GDL code, advancing automated game creation.

Findings

Generated diverse simplified boardgames using evolutionary algorithms

Successfully translated generated games into GDL code

Proposed method enhances game diversity for GGP tournaments

Abstract

We present initial research towards procedural generation of Simplified Boardgames and translating them into an efficient GDL code. This is a step towards establishing Simplified Boardgames as a comparison class for General Game Playing agents. To generate playable, human readable, and balanced chess-like games we use an adaptive evolutionary algorithm with the fitness function based on simulated playouts. In future, we plan to use the proposed method to diversify and extend the set of GGP tournament games by those with fully automatically generated rules.