{"title":"自治系统中的目标导向行为","authors":"Peiya Liu","doi":"10.1109/TAI.1990.130301","DOIUrl":null,"url":null,"abstract":"A discussion is given on how situation-driven autonomous systems can look ahead to resolve goal interactions and conflicts and to find a better way to achieve goals. Several lookahead schemes are examined implicitly in current autonomous systems. A rational reconstruction of a novel scheme in action selection dynamics is outlined for a better run-time planner to obtain goal-oriented behavior. It is shown that this reconstruction results in an action arbitration scheme having a more informative run-time lookahead for resolving goal interactions and conflicts without loss of its continual 'replanning' capability.<<ETX>>","PeriodicalId":366276,"journal":{"name":"[1990] Proceedings of the 2nd International IEEE Conference on Tools for Artificial Intelligence","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1990-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Goal-oriented behavior in autonomous systems\",\"authors\":\"Peiya Liu\",\"doi\":\"10.1109/TAI.1990.130301\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A discussion is given on how situation-driven autonomous systems can look ahead to resolve goal interactions and conflicts and to find a better way to achieve goals. Several lookahead schemes are examined implicitly in current autonomous systems. A rational reconstruction of a novel scheme in action selection dynamics is outlined for a better run-time planner to obtain goal-oriented behavior. It is shown that this reconstruction results in an action arbitration scheme having a more informative run-time lookahead for resolving goal interactions and conflicts without loss of its continual 'replanning' capability.<<ETX>>\",\"PeriodicalId\":366276,\"journal\":{\"name\":\"[1990] Proceedings of the 2nd International IEEE Conference on Tools for Artificial Intelligence\",\"volume\":\"11 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1990-11-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"[1990] Proceedings of the 2nd International IEEE Conference on Tools for Artificial Intelligence\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/TAI.1990.130301\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"[1990] Proceedings of the 2nd International IEEE Conference on Tools for Artificial Intelligence","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TAI.1990.130301","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A discussion is given on how situation-driven autonomous systems can look ahead to resolve goal interactions and conflicts and to find a better way to achieve goals. Several lookahead schemes are examined implicitly in current autonomous systems. A rational reconstruction of a novel scheme in action selection dynamics is outlined for a better run-time planner to obtain goal-oriented behavior. It is shown that this reconstruction results in an action arbitration scheme having a more informative run-time lookahead for resolving goal interactions and conflicts without loss of its continual 'replanning' capability.<>