MMAIApr 30, 2017

Deriving Quests from Open World Mechanics

arXiv:1705.00341v125 citations
Originality Incremental advance
AI Analysis

This addresses the issue of player aimlessness in open world games by automating quest generation, though it is incremental as it builds on existing procedural content generation methods.

The paper tackled the problem of generating quests organically from open world game mechanics, specifically in Minecraft, by formalizing game logic into logical rules and using static analysis to algorithmically place achievements based on gameplay actions.

Open world games present players with more freedom than games with linear progression structures. However, without clearly-defined objectives, they often leave players without a sense of purpose. Most of the time, quests and objectives are hand-authored and overlaid atop an open world's mechanics. But what if they could be generated organically from the gameplay itself? The goal of our project was to develop a model of the mechanics in Minecraft that could be used to determine the ideal placement of objectives in an open world setting. We formalized the game logic of Minecraft in terms of logical rules that can be manipulated in two ways: they may be executed to generate graphs representative of the player experience when playing an open world game with little developer direction; and they may be statically analyzed to determine dependency orderings, feedback loops, and bottlenecks. These analyses may then be used to place achievements on gameplay actions algorithmically.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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