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20042025
most citedDeep Learning for Procedural Content Generation

143 citations · 1.3k across the 89 of their papers we have counts for

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64 papers · 1 filter

cs.AI2025

The Procedural Content Generation Benchmark: An Open-source Testbed for Generative Challenges in Games

Ahmed Khalifa, Roberto Gallotta, Matthew Barthet +3

This paper introduces the Procedural Content Generation Benchmark for evaluating generative algorithms on different game content creation tasks. The benchmark comes with 12 game-re…

cs.AI2023

Benchmarking Robustness and Generalization in Multi-Agent Systems: A Case Study on Neural MMO

Yangkun Chen, Joseph Suarez, Junjie Zhang +18

We present the results of the second Neural MMO challenge, hosted at IJCAI 2022, which received 1600+ submissions. This competition targets robustness and generalization in multi-a…

cs.AI2023

Generating Redstone Style Cities in Minecraft

Shuo Huang, Chengpeng Hu, Julian Togelius +1

Procedurally generating cities in Minecraft provides players more diverse scenarios and could help understand and improve the design of cities in other digital worlds and the real…

cs.AI2023

ChatGPT4PCG Competition: Character-like Level Generation for Science Birds

Pittawat Taveekitworachai, Febri Abdullah, Mury F. Dewantoro +3

This paper presents the first ChatGPT4PCG Competition at the 2023 IEEE Conference on Games. The objective of this competition is for participants to create effective prompts for Ch…

cs.AI2022

Keke AI Competition: Solving puzzle levels in a dynamically changing mechanic space

M Charity, Julian Togelius

The Keke AI Competition introduces an artificial agent competition for the game Baba is You - a Sokoban-like puzzle game where players can create rules that influence the mechanics…

cs.AI2022★ 1 cited

Aesthetic Bot: Interactively Evolving Game Maps on Twitter

M Charity, Julian Togelius

This paper describes the implementation of the Aesthetic Bot, an automated Twitter account that posts images of small game maps that are either user-made or generated from an evolu…