Ahmed S. Hefny, Ayat A. Hatem, Mahmoud Shalaby, Amir Atiya
{"title":"Cerberus:将监督和强化学习技术应用于夺旗游戏","authors":"Ahmed S. Hefny, Ayat A. Hatem, Mahmoud Shalaby, Amir Atiya","doi":"10.1609/aiide.v4i1.18694","DOIUrl":null,"url":null,"abstract":"Applying machine learning techniques to real-time computer games is an active research field. In this paper we present Cerberus, a machine learning framework for team-based Capture The Flag (CTF) games. This framework utilizes reinforcement learning to select high-level actions that achieve best team behaviour and utilizes neural networks to control fighting behaviour of team individuals. Our proposed framework also combines waypoints and influence maps for effective path planning","PeriodicalId":249108,"journal":{"name":"Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment","volume":"74 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-09-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Cerberus: Applying Supervised and Reinforcement Learning Techniques to Capture the Flag Games\",\"authors\":\"Ahmed S. Hefny, Ayat A. Hatem, Mahmoud Shalaby, Amir Atiya\",\"doi\":\"10.1609/aiide.v4i1.18694\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Applying machine learning techniques to real-time computer games is an active research field. In this paper we present Cerberus, a machine learning framework for team-based Capture The Flag (CTF) games. This framework utilizes reinforcement learning to select high-level actions that achieve best team behaviour and utilizes neural networks to control fighting behaviour of team individuals. Our proposed framework also combines waypoints and influence maps for effective path planning\",\"PeriodicalId\":249108,\"journal\":{\"name\":\"Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment\",\"volume\":\"74 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-09-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1609/aiide.v4i1.18694\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1609/aiide.v4i1.18694","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
将机器学习技术应用于实时电脑游戏是一个活跃的研究领域。在本文中,我们介绍了Cerberus,这是一个基于团队的Capture The Flag (CTF)游戏的机器学习框架。该框架利用强化学习选择实现最佳团队行为的高级行动,并利用神经网络控制团队个人的战斗行为。我们提出的框架还结合了路点和影响图,以实现有效的路径规划
Cerberus: Applying Supervised and Reinforcement Learning Techniques to Capture the Flag Games
Applying machine learning techniques to real-time computer games is an active research field. In this paper we present Cerberus, a machine learning framework for team-based Capture The Flag (CTF) games. This framework utilizes reinforcement learning to select high-level actions that achieve best team behaviour and utilizes neural networks to control fighting behaviour of team individuals. Our proposed framework also combines waypoints and influence maps for effective path planning