{"title":"基于高效行为分化模型的自适应智能体","authors":"M. Gongora, D. Irvine","doi":"10.1109/ANDESCON.2010.5630082","DOIUrl":null,"url":null,"abstract":"This paper describes our novel methodology for the creation of efficient AI based Agents capable of adapting. We use AI concepts established and used in the implementation of character behaviour for games, such as the Belief-Desire-Intention model and Finite State Machines. A discussion on their role in efficient agent behaviour encoding is presented. We then suggest a novel differentiated combination of these techniques to enable the process of self-adaptation for intelligent agents used to represent characters in virtual environments.","PeriodicalId":359559,"journal":{"name":"2010 IEEE ANDESCON","volume":"195 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Adaptive intelligent agents based on efficient behaviour differentiation models\",\"authors\":\"M. Gongora, D. Irvine\",\"doi\":\"10.1109/ANDESCON.2010.5630082\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper describes our novel methodology for the creation of efficient AI based Agents capable of adapting. We use AI concepts established and used in the implementation of character behaviour for games, such as the Belief-Desire-Intention model and Finite State Machines. A discussion on their role in efficient agent behaviour encoding is presented. We then suggest a novel differentiated combination of these techniques to enable the process of self-adaptation for intelligent agents used to represent characters in virtual environments.\",\"PeriodicalId\":359559,\"journal\":{\"name\":\"2010 IEEE ANDESCON\",\"volume\":\"195 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-11-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 IEEE ANDESCON\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ANDESCON.2010.5630082\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 IEEE ANDESCON","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ANDESCON.2010.5630082","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Adaptive intelligent agents based on efficient behaviour differentiation models
This paper describes our novel methodology for the creation of efficient AI based Agents capable of adapting. We use AI concepts established and used in the implementation of character behaviour for games, such as the Belief-Desire-Intention model and Finite State Machines. A discussion on their role in efficient agent behaviour encoding is presented. We then suggest a novel differentiated combination of these techniques to enable the process of self-adaptation for intelligent agents used to represent characters in virtual environments.