Constructive generation methods for dungeons and levels

Procedural Content Generation through Quality Diversity

“…However, several key properties of QD algorithms make them better suited than 'typical' SBPCG approaches. Moreover, PCG-QD is compared with popular approaches for generating games in academia and in the industry, namely machine learning (PCGML) [24] and constructive algorithms [25] respectively.…”

Reasoning in Highly Reactive Environments

“…As a side research topic we investigated to what extent the ASP-based approach is scalable enough for industrial contexts in the field of video games, by proposing a Unity extension capable to automatically generate dungeons maps 4 . In this context we first investigated over the usage of a partition-based generation technique [25], then we proposed a multiple step-generation approach, set in the context of the 2-D caves generation domain, where each step is declaratively controlled by an ASP specification. With respect to existing literature [23,26], our approach promises to be better scalable to real contexts with higher size mazes; experiments aimed at confirming that are currently ongoing.…”

Two-step constructive approaches for dungeon generation

“…While research on level generation focuses on level generators based on stochastic search [14], constraint solving [11,12], or machine learning [13], level generation in published games is mostly carried out via constructive algorithms. Unlike generate-and-test processes, constructive generators do not evaluate and re-generate output; for example, cellular automata and grammars can be used for constructive generation, as well as more freeform approaches such as diggers [10]. Such generators are computationally lightweight since they do not evaluate their generated output.…”

“…We start our exploration in procedural level generation of Minidungeons 2 by reviewing how constructive map generation has been done in other games. Based on Shaker et al [10], popular methods for generating dungeons include binary state partitioning, cellular automata and digger agents. A digger agent is placed in a dungeon filled with impassable blocks (often in a random position), and removes the block it is in while moving to adjacent tiles following random or rule-based strategies.…”