{"title":"Inheritance reasoning in connectionist networks","authors":"M. Jones, G. A. Story","doi":"10.1109/IJCNN.1989.118335","DOIUrl":null,"url":null,"abstract":"Summary form only given, as follows. A bidirectional network model is described for inheritance reasoning which processes queries by combinations of top-down and bottom-up reasoning. The model, which is based on theoretical work in nonmonotonic reasoning, permits multiple inheritance paths in acyclic inheritance theories and allows an arbitrary preference relation among the inferences in the theory (to handle exceptions, for example). Unlike other inheritance models which compute extensions serially (maximally consistent models), the network gains substantially more parallelism by simultaneously reasoning in multiple extensions when possible.<<ETX>>","PeriodicalId":199877,"journal":{"name":"International 1989 Joint Conference on Neural Networks","volume":"35 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International 1989 Joint Conference on Neural Networks","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IJCNN.1989.118335","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Summary form only given, as follows. A bidirectional network model is described for inheritance reasoning which processes queries by combinations of top-down and bottom-up reasoning. The model, which is based on theoretical work in nonmonotonic reasoning, permits multiple inheritance paths in acyclic inheritance theories and allows an arbitrary preference relation among the inferences in the theory (to handle exceptions, for example). Unlike other inheritance models which compute extensions serially (maximally consistent models), the network gains substantially more parallelism by simultaneously reasoning in multiple extensions when possible.<>