{"title":"迈向稳健的分层学习","authors":"W. Richert, B. Kleinjohann","doi":"10.1109/CONIELECOMP.2007.111","DOIUrl":null,"url":null,"abstract":"In his landmark work introducing layered learning Stone presented a new way of handling complex application domains suitable especially for mobile robots. We extend his framework by introducing robust layered learning- a framework that is able to handle system and environmental changes at every layer. We present first results of a lower level implementation of such a framework for mobile robots and discuss how all available sources of information regarding unforeseen changes can be integrated in such a framework in order to reach maximal robustness.","PeriodicalId":288478,"journal":{"name":"Third International Conference on Autonomic and Autonomous Systems (ICAS'07)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Towards Robust Layered Learning\",\"authors\":\"W. Richert, B. Kleinjohann\",\"doi\":\"10.1109/CONIELECOMP.2007.111\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In his landmark work introducing layered learning Stone presented a new way of handling complex application domains suitable especially for mobile robots. We extend his framework by introducing robust layered learning- a framework that is able to handle system and environmental changes at every layer. We present first results of a lower level implementation of such a framework for mobile robots and discuss how all available sources of information regarding unforeseen changes can be integrated in such a framework in order to reach maximal robustness.\",\"PeriodicalId\":288478,\"journal\":{\"name\":\"Third International Conference on Autonomic and Autonomous Systems (ICAS'07)\",\"volume\":\"15 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-06-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Third International Conference on Autonomic and Autonomous Systems (ICAS'07)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CONIELECOMP.2007.111\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Third International Conference on Autonomic and Autonomous Systems (ICAS'07)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CONIELECOMP.2007.111","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
In his landmark work introducing layered learning Stone presented a new way of handling complex application domains suitable especially for mobile robots. We extend his framework by introducing robust layered learning- a framework that is able to handle system and environmental changes at every layer. We present first results of a lower level implementation of such a framework for mobile robots and discuss how all available sources of information regarding unforeseen changes can be integrated in such a framework in order to reach maximal robustness.