{"title":"大型人工神经网络(LANNET)","authors":"D. Guinn","doi":"10.1109/TME.1963.4323078","DOIUrl":null,"url":null,"abstract":"This report describes the implementation of a high speed self-organizing system based on the reinforcement principle. The self-organizing binary logical network is used as the primary component in the system. The learning system is a 1024 decision element netwolk with a general purpose program to enable the operator to simulate a large number of problems to study machine learning. The simulation of a maze runner problem and the results of some preliminary machine evaluation are presented. The system was developed for the Aeronautical Systems Division's Electronic Technology Laboratory to study complex biological problems.","PeriodicalId":199455,"journal":{"name":"IEEE Transactions on Military Electronics","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1963-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Large Artificial Nerve Net (LANNET)\",\"authors\":\"D. Guinn\",\"doi\":\"10.1109/TME.1963.4323078\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This report describes the implementation of a high speed self-organizing system based on the reinforcement principle. The self-organizing binary logical network is used as the primary component in the system. The learning system is a 1024 decision element netwolk with a general purpose program to enable the operator to simulate a large number of problems to study machine learning. The simulation of a maze runner problem and the results of some preliminary machine evaluation are presented. The system was developed for the Aeronautical Systems Division's Electronic Technology Laboratory to study complex biological problems.\",\"PeriodicalId\":199455,\"journal\":{\"name\":\"IEEE Transactions on Military Electronics\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1963-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Transactions on Military Electronics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/TME.1963.4323078\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Military Electronics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TME.1963.4323078","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
This report describes the implementation of a high speed self-organizing system based on the reinforcement principle. The self-organizing binary logical network is used as the primary component in the system. The learning system is a 1024 decision element netwolk with a general purpose program to enable the operator to simulate a large number of problems to study machine learning. The simulation of a maze runner problem and the results of some preliminary machine evaluation are presented. The system was developed for the Aeronautical Systems Division's Electronic Technology Laboratory to study complex biological problems.
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