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Feliks Jakimow

Generating City Layouts Using Artificial Neural Networks

Synopsis

Artificial neural networks are commonplace in modern applications due to their adaptability in solving new and old problems - especially ones that are traditionally tedious.

By using a gated recurrent unit (GRU) encoder-decoder network, countless design features in a city's design can be accurately captured. Used in conjunction with procedural generation, a full city layout can be achieved with little effort from the user, only requiring them to choose a city located anywhere in the world.

Project info

  • Developer Feliks Jakimow
  • Showcase year 2021
  • Programme Computer Game Applications Development

Generating City Layouts Using Artificial Neural Networks

Manually creating a city layout is tedious; artificial neural networks can be used to capture a city's layout accurately, with minimal input from the user.

Motivation

I've had an interest in using procedural generation to generate unique, sometimes surreal, places for people to explore - and to me cities have been a missing link in this field. You could get very good looking environments with conventional methods but they never had much life to them as they lacked man-made structures. I hope to plug the gap with this project!

Credits

鈥淕enerating City Layouts Using Artificial Neural Networks鈥 is a 2021 Digital Graduate Show project by聽Feliks Jakimow, a Computer Game Applications Development student at Abertay University.聽聽聽聽聽聽

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Feliks Jakimow

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