Automatic Generation of Falling Block Puzzle Games with Multiplayer Strategic Elements

Abstract

Advancements in game content generation have progressed, but research on automatic game rule generation remains limited, especially for multiplayer games emphasizing strategy. This study targets falling block puzzle games, proposing a description language to generate strategic competitive rules. By randomly selecting rule elements under constraints, the method ensures functional gameplay with interference mechanics. Evaluations confirmed stable rule generation, and user experiments showed most rules provided strategic depth. This demonstrates the method's effectiveness in generating stable, strategy-focused multiplayer game rules.