{"title":"信念-愿望-意图代理的算法调试方法","authors":"Tobias Ahlbrecht","doi":"10.1007/s10472-023-09843-4","DOIUrl":null,"url":null,"abstract":"<div><p>Debugging agent systems can be rather difficult. It is often noted as one of the most time-consuming tasks during the development of cognitive agents. Algorithmic (or declarative) debugging is a semi-automatic technique, where the developer is asked questions by the debugger in order to locate the source of an error. We present how this can be applied in the context of a BDI agent language, demonstrate how it can speed up or simplify the debugging process and reflect on its advantages and limitations.</p></div>","PeriodicalId":7971,"journal":{"name":"Annals of Mathematics and Artificial Intelligence","volume":"92 4","pages":"797 - 814"},"PeriodicalIF":1.2000,"publicationDate":"2023-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s10472-023-09843-4.pdf","citationCount":"0","resultStr":"{\"title\":\"An algorithmic debugging approach for belief-desire-intention agents\",\"authors\":\"Tobias Ahlbrecht\",\"doi\":\"10.1007/s10472-023-09843-4\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Debugging agent systems can be rather difficult. It is often noted as one of the most time-consuming tasks during the development of cognitive agents. Algorithmic (or declarative) debugging is a semi-automatic technique, where the developer is asked questions by the debugger in order to locate the source of an error. We present how this can be applied in the context of a BDI agent language, demonstrate how it can speed up or simplify the debugging process and reflect on its advantages and limitations.</p></div>\",\"PeriodicalId\":7971,\"journal\":{\"name\":\"Annals of Mathematics and Artificial Intelligence\",\"volume\":\"92 4\",\"pages\":\"797 - 814\"},\"PeriodicalIF\":1.2000,\"publicationDate\":\"2023-05-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://link.springer.com/content/pdf/10.1007/s10472-023-09843-4.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Annals of Mathematics and Artificial Intelligence\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://link.springer.com/article/10.1007/s10472-023-09843-4\",\"RegionNum\":4,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Annals of Mathematics and Artificial Intelligence","FirstCategoryId":"94","ListUrlMain":"https://link.springer.com/article/10.1007/s10472-023-09843-4","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
An algorithmic debugging approach for belief-desire-intention agents
Debugging agent systems can be rather difficult. It is often noted as one of the most time-consuming tasks during the development of cognitive agents. Algorithmic (or declarative) debugging is a semi-automatic technique, where the developer is asked questions by the debugger in order to locate the source of an error. We present how this can be applied in the context of a BDI agent language, demonstrate how it can speed up or simplify the debugging process and reflect on its advantages and limitations.
期刊介绍:
Annals of Mathematics and Artificial Intelligence presents a range of topics of concern to scholars applying quantitative, combinatorial, logical, algebraic and algorithmic methods to diverse areas of Artificial Intelligence, from decision support, automated deduction, and reasoning, to knowledge-based systems, machine learning, computer vision, robotics and planning.
The journal features collections of papers appearing either in volumes (400 pages) or in separate issues (100-300 pages), which focus on one topic and have one or more guest editors.
Annals of Mathematics and Artificial Intelligence hopes to influence the spawning of new areas of applied mathematics and strengthen the scientific underpinnings of Artificial Intelligence.