{"title":"在Jason中量化软件设计原则和性能之间的关系:模拟移动机器人的案例研究","authors":"Patrick Gavigan, Babak Esfandiari","doi":"10.1007/s10472-023-09844-3","DOIUrl":null,"url":null,"abstract":"<div><p>We investigated the relationship between various design approaches of AgentSpeak code for Jason Beliefs-Desires-Intentions (BDI) agents and their performance in a simulated automotive collision avoidance scenario. Also explored was how the approaches affected software maintainability, assessed through coupling, cohesion, and cyclomatic complexity. We then compared each agent’s performance, specifically their reasoning cycle duration and their responsiveness. Our findings revealed that agents with looser coupling and higher cohesion are more responsive to stimuli, implying that more maintainable AgentSpeak code can result in better performing agents. Performance was inversely related to cyclomatic complexity.</p></div>","PeriodicalId":7971,"journal":{"name":"Annals of Mathematics and Artificial Intelligence","volume":"92 4","pages":"775 - 795"},"PeriodicalIF":1.2000,"publicationDate":"2023-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Quantifying the relationship between software design principles and performance in Jason: a case study with simulated mobile robots\",\"authors\":\"Patrick Gavigan, Babak Esfandiari\",\"doi\":\"10.1007/s10472-023-09844-3\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>We investigated the relationship between various design approaches of AgentSpeak code for Jason Beliefs-Desires-Intentions (BDI) agents and their performance in a simulated automotive collision avoidance scenario. Also explored was how the approaches affected software maintainability, assessed through coupling, cohesion, and cyclomatic complexity. We then compared each agent’s performance, specifically their reasoning cycle duration and their responsiveness. Our findings revealed that agents with looser coupling and higher cohesion are more responsive to stimuli, implying that more maintainable AgentSpeak code can result in better performing agents. Performance was inversely related to cyclomatic complexity.</p></div>\",\"PeriodicalId\":7971,\"journal\":{\"name\":\"Annals of Mathematics and Artificial Intelligence\",\"volume\":\"92 4\",\"pages\":\"775 - 795\"},\"PeriodicalIF\":1.2000,\"publicationDate\":\"2023-06-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"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/s10472-023-09844-3\",\"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/s10472-023-09844-3","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
我们研究了 Jason Beliefs-Desires-Intentions (BDI) 代理的 AgentSpeak 代码的各种设计方法与其在模拟汽车防撞场景中的性能之间的关系。此外，我们还探讨了这些方法如何影响软件的可维护性，并通过耦合度、内聚度和循环复杂度进行了评估。然后，我们比较了每个代理的性能，特别是它们的推理周期持续时间和响应速度。我们的研究结果表明，耦合度较低和内聚度较高的代理对刺激的反应速度更快，这意味着可维护性更高的 AgentSpeak 代码可以产生性能更好的代理。性能与循环复杂度成反比。
Quantifying the relationship between software design principles and performance in Jason: a case study with simulated mobile robots
We investigated the relationship between various design approaches of AgentSpeak code for Jason Beliefs-Desires-Intentions (BDI) agents and their performance in a simulated automotive collision avoidance scenario. Also explored was how the approaches affected software maintainability, assessed through coupling, cohesion, and cyclomatic complexity. We then compared each agent’s performance, specifically their reasoning cycle duration and their responsiveness. Our findings revealed that agents with looser coupling and higher cohesion are more responsive to stimuli, implying that more maintainable AgentSpeak code can result in better performing agents. Performance was inversely related to cyclomatic complexity.
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.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
