Febri Abdullah;Pittawat Taveekitworachai;Mury F. Dewantoro;Ruck Thawonmas;Julian Togelius;Jochen Renz
{"title":"The First ChatGPT4PCG Competition","authors":"Febri Abdullah;Pittawat Taveekitworachai;Mury F. Dewantoro;Ruck Thawonmas;Julian Togelius;Jochen Renz","doi":"10.1109/TG.2024.3376429","DOIUrl":null,"url":null,"abstract":"This article summarizes the first ChatGPT4PCG competition held at the 2023 IEEE Conference on Games. The goal of the competition is to explore emergent abilities of publicly available large language models (LLMs) in performing complex tasks related to procedural content generation, specifically physics-based level generation for \n<italic>Angry Birds</i>\n-like games. Participants are tasked with submitting their prompts for ChatGPT to generate \n<italic>Angry Birds</i>\n-like game structures that resemble English uppercase characters. A structure is a collection of stacked game objects comprising a part of an entire \n<italic>Angry Birds</i>\n-like level. A prompt is an input for LLMs, including ChatGPT. Two evaluation metrics, i.e., stability and similarity, are used to evaluate the submitted prompts. Stability measures the sturdiness of a structure to withstand in-game gravity, while similarity measures a structure's resemblance to the target character. With such evaluation, participants are challenged to produce not only character-like but also stable structures by utilizing prompt engineering techniques. Finally, the competition's results are discussed to provide valuable insights for future studies and competitions.","PeriodicalId":55977,"journal":{"name":"IEEE Transactions on Games","volume":"16 4","pages":"971-980"},"PeriodicalIF":1.7000,"publicationDate":"2024-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Games","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10470422/","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 0
Abstract
This article summarizes the first ChatGPT4PCG competition held at the 2023 IEEE Conference on Games. The goal of the competition is to explore emergent abilities of publicly available large language models (LLMs) in performing complex tasks related to procedural content generation, specifically physics-based level generation for
Angry Birds
-like games. Participants are tasked with submitting their prompts for ChatGPT to generate
Angry Birds
-like game structures that resemble English uppercase characters. A structure is a collection of stacked game objects comprising a part of an entire
Angry Birds
-like level. A prompt is an input for LLMs, including ChatGPT. Two evaluation metrics, i.e., stability and similarity, are used to evaluate the submitted prompts. Stability measures the sturdiness of a structure to withstand in-game gravity, while similarity measures a structure's resemblance to the target character. With such evaluation, participants are challenged to produce not only character-like but also stable structures by utilizing prompt engineering techniques. Finally, the competition's results are discussed to provide valuable insights for future studies and competitions.