Cellular Automata – Procedural Map Generator

Introduction

As a lifelong gamer, I’ve always been intrigued by the worlds that unfold before me on the screen. Digging into how these worlds are constructed led me to the fascinating realm of procedural generation. In this weekend project, I applied the concept of cellular automata to create randomized 2D maps in Unity. This serves as a stepping stone to more complex, feature-rich maps and even 3D worlds.

Cellular Automatons are widely used as procedural map generators in videogames. In this example made with Unity, you can see a random generated map every few seconds.

Technologies Used

  • Software: Unity
  • Programming Language: C#

Project Goals

  1. Create a basic 2D map using cellular automata.
  2. Display a newly generated map every few seconds within the Unity environment.

Challenges Faced

  • Algorithm Complexity: Cellular automata can become intricate, and ensuring that the algorithm was correctly implemented was a challenge.
  • Limited Time: Being a weekend project, time was a constraint for diving deeper into more advanced features.

Solutions and Approaches

  • Unity and C#: Leveraged Unity’s robust platform and C#’s versatility to quickly prototype the algorithm.
  • Iterative Development: Rolled out the basic version first with plans for iterative improvements.

Key Features

  • Real-time Map Generation: The Unity environment displays a new, randomly generated 2D map every few seconds.
  • Scalability: The implemented algorithm is language-agnostic and can be ported to different programming languages or platforms.

Outcomes and Impact

  • Proof-of-Concept: Successfully created a 2D map generation utility using cellular automata.
  • Deeper Understanding: Gained insights into procedural algorithms commonly used in video games.

Lessons Learned

  • Importance of Algorithms: Recognized the role of specialized algorithms like cellular automata in the gaming industry.
  • Iterative Approach: Learned that even a short weekend project can yield significant insights and serve as a foundation for future exploration.

Future Directions

  • 3D Map Generation: Plan to extend this to 3D environments.
  • Advanced Features: Aim to incorporate constraints such as start and end points, and specific room sizes.

Release Date

2015