Alberto Almagro;Juan Carlos Llamas-Núñez;Antonio A. Sánchez-Ruiz;Belén Díaz-Agudo
{"title":"Collaborative AI in the Geometry Friends Game Competition","authors":"Alberto Almagro;Juan Carlos Llamas-Núñez;Antonio A. Sánchez-Ruiz;Belén Díaz-Agudo","doi":"10.1109/TG.2024.3487309","DOIUrl":null,"url":null,"abstract":"<italic>Geometry Friends</i> is a collaborative platform game featuring two agents, a circle and a rectangle, navigating through physics-driven levels to collect diamonds. Each level presents challenges in the form of obstacles and diamonds arranged in different configurations that forces the agents to cooperate. In this article, we describe the Universidad Complutense de Madrid (UCM) agents, that participated in the 2023 <italic>Geometry Friends</i> AI Competition with excellent results, especially in the collaborative track. Our approach combines level analysis, motion simulation, abstract planning, scripted actions, reinforcement learning, and different types of agent interaction. The contributions are versatile and potentially applicable to other collaborative platform games.","PeriodicalId":55977,"journal":{"name":"IEEE Transactions on Games","volume":"17 2","pages":"408-418"},"PeriodicalIF":2.8000,"publicationDate":"2024-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10737403","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Games","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10737403/","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
Geometry Friends is a collaborative platform game featuring two agents, a circle and a rectangle, navigating through physics-driven levels to collect diamonds. Each level presents challenges in the form of obstacles and diamonds arranged in different configurations that forces the agents to cooperate. In this article, we describe the Universidad Complutense de Madrid (UCM) agents, that participated in the 2023 Geometry Friends AI Competition with excellent results, especially in the collaborative track. Our approach combines level analysis, motion simulation, abstract planning, scripted actions, reinforcement learning, and different types of agent interaction. The contributions are versatile and potentially applicable to other collaborative platform games.