{"title":"基于agent的自主规划模型","authors":"F. Amato, Francesco Moscato","doi":"10.1109/CISIS.2016.135","DOIUrl":null,"url":null,"abstract":"Distributed autonomous elements like sensors networks, intelligent devices etc. are nowadays widely used. Here, one of the most difficult task is the automatic re-planning when something goes wrong: new planning algorithms have to be coped with existing ones in order to fulfill performance and soundness requirements. In this work we present a modelling methodology and a planning technique based on multi-agent models. The planning methodology exploits both classical and a new counter-example based approaches in order to build an effective multi-expert system able to face with increasing complexity of these systems, implementing procedures that make possible the reaching of desired goals within temporal constraints.","PeriodicalId":249236,"journal":{"name":"2016 10th International Conference on Complex, Intelligent, and Software Intensive Systems (CISIS)","volume":"61 3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An Agent-Based Model for Autonomous Planning\",\"authors\":\"F. Amato, Francesco Moscato\",\"doi\":\"10.1109/CISIS.2016.135\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Distributed autonomous elements like sensors networks, intelligent devices etc. are nowadays widely used. Here, one of the most difficult task is the automatic re-planning when something goes wrong: new planning algorithms have to be coped with existing ones in order to fulfill performance and soundness requirements. In this work we present a modelling methodology and a planning technique based on multi-agent models. The planning methodology exploits both classical and a new counter-example based approaches in order to build an effective multi-expert system able to face with increasing complexity of these systems, implementing procedures that make possible the reaching of desired goals within temporal constraints.\",\"PeriodicalId\":249236,\"journal\":{\"name\":\"2016 10th International Conference on Complex, Intelligent, and Software Intensive Systems (CISIS)\",\"volume\":\"61 3 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 10th International Conference on Complex, Intelligent, and Software Intensive Systems (CISIS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CISIS.2016.135\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 10th International Conference on Complex, Intelligent, and Software Intensive Systems (CISIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CISIS.2016.135","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Distributed autonomous elements like sensors networks, intelligent devices etc. are nowadays widely used. Here, one of the most difficult task is the automatic re-planning when something goes wrong: new planning algorithms have to be coped with existing ones in order to fulfill performance and soundness requirements. In this work we present a modelling methodology and a planning technique based on multi-agent models. The planning methodology exploits both classical and a new counter-example based approaches in order to build an effective multi-expert system able to face with increasing complexity of these systems, implementing procedures that make possible the reaching of desired goals within temporal constraints.