{"title":"A/sup 2/:面向多智能体约束满足问题的面向智能体的编程体系结构","authors":"E. Freeman","doi":"10.1109/TAI.1990.130446","DOIUrl":null,"url":null,"abstract":"An agent-oriented programming metaphor is used to extend the analytic capabilities of a constraint logic programming system, such as CLP(R), to the domain of multi-agent constraint satisfaction problems. The resulting implementation provides a set of system primitives, which support at a rudimentary level, the maintenance of private knowledge bases, inter-agent communications, constraint driven multi-agent consensus formation, functional inheritance via 'cloning' and a choice of inheritance lattice search optimization mechanisms, allowing knowledge engineers to make speed vs. flexibility and functional dependence vs. independence trade-offs. A general architecture for agent-oriented programming systems is presented, and some of the more salient aspects of its CLP(R) implementation are summarized.<<ETX>>","PeriodicalId":366276,"journal":{"name":"[1990] Proceedings of the 2nd International IEEE Conference on Tools for Artificial Intelligence","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1990-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":"{\"title\":\"A/sup 2/: an agent-oriented programming architecture for multi-agent constraint satisfaction problems\",\"authors\":\"E. Freeman\",\"doi\":\"10.1109/TAI.1990.130446\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"An agent-oriented programming metaphor is used to extend the analytic capabilities of a constraint logic programming system, such as CLP(R), to the domain of multi-agent constraint satisfaction problems. The resulting implementation provides a set of system primitives, which support at a rudimentary level, the maintenance of private knowledge bases, inter-agent communications, constraint driven multi-agent consensus formation, functional inheritance via 'cloning' and a choice of inheritance lattice search optimization mechanisms, allowing knowledge engineers to make speed vs. flexibility and functional dependence vs. independence trade-offs. A general architecture for agent-oriented programming systems is presented, and some of the more salient aspects of its CLP(R) implementation are summarized.<<ETX>>\",\"PeriodicalId\":366276,\"journal\":{\"name\":\"[1990] Proceedings of the 2nd International IEEE Conference on Tools for Artificial Intelligence\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1990-11-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"10\",\"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.1990.130446\",\"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.1990.130446","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A/sup 2/: an agent-oriented programming architecture for multi-agent constraint satisfaction problems
An agent-oriented programming metaphor is used to extend the analytic capabilities of a constraint logic programming system, such as CLP(R), to the domain of multi-agent constraint satisfaction problems. The resulting implementation provides a set of system primitives, which support at a rudimentary level, the maintenance of private knowledge bases, inter-agent communications, constraint driven multi-agent consensus formation, functional inheritance via 'cloning' and a choice of inheritance lattice search optimization mechanisms, allowing knowledge engineers to make speed vs. flexibility and functional dependence vs. independence trade-offs. A general architecture for agent-oriented programming systems is presented, and some of the more salient aspects of its CLP(R) implementation are summarized.<>