信念-愿望-意图代理的算法调试方法

IF 1.2 4区 计算机科学 Q4 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Annals of Mathematics and Artificial Intelligence Pub Date : 2023-05-05 DOI:10.1007/s10472-023-09843-4
Tobias Ahlbrecht
{"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}
引用次数: 0

摘要

调试代理系统可能相当困难。在认知代理的开发过程中,调试往往是最耗时的工作之一。算法(或声明式)调试是一种半自动技术,调试器会向开发人员提出问题,以便找出错误的根源。我们将介绍如何将其应用于 BDI 代理语言,演示如何加快或简化调试过程,并对其优势和局限性进行思考。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
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.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Annals of Mathematics and Artificial Intelligence
Annals of Mathematics and Artificial Intelligence 工程技术-计算机:人工智能
CiteScore
3.00
自引率
8.30%
发文量
37
审稿时长
>12 weeks
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.
期刊最新文献
Time-penalised trees (TpT): introducing a new tree-based data mining algorithm for time-varying covariates Conformal test martingales for hypergraphical models Costly information providing in binary contests Tumato 2.0 - a constraint-based planning approach for safe and robust robot behavior Calibration methods in imbalanced binary classification
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1