{"title":"大脑启发尖峰神经网络中的终身学习和不断演化的联想记忆","authors":"Nikola K Kasabov","doi":"10.15406/mojabb.2024.08.00208","DOIUrl":null,"url":null,"abstract":"The paper argues that evolving associative memories (EAM), that are manifested in all biological systems and realised in the human brain through life-long learning (LLL), can be realised in brain-inspired computational architectures based on spiking neural networks (SNN). The paper points to the importance of the duality of the concepts of EAM and LLL for future AI systems.","PeriodicalId":411709,"journal":{"name":"MOJ Applied Bionics and Biomechanics","volume":" 8","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Life-long learning and evolving associative memories in brain-inspired spiking neural networks\",\"authors\":\"Nikola K Kasabov\",\"doi\":\"10.15406/mojabb.2024.08.00208\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The paper argues that evolving associative memories (EAM), that are manifested in all biological systems and realised in the human brain through life-long learning (LLL), can be realised in brain-inspired computational architectures based on spiking neural networks (SNN). The paper points to the importance of the duality of the concepts of EAM and LLL for future AI systems.\",\"PeriodicalId\":411709,\"journal\":{\"name\":\"MOJ Applied Bionics and Biomechanics\",\"volume\":\" 8\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-05-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"MOJ Applied Bionics and Biomechanics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.15406/mojabb.2024.08.00208\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"MOJ Applied Bionics and Biomechanics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.15406/mojabb.2024.08.00208","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
论文认为，进化关联记忆（EAM）体现在所有生物系统中，并通过终身学习（LLL）在人脑中得以实现，它可以在基于尖峰神经网络（SNN）的脑启发计算架构中得以实现。论文指出了 EAM 和 LLL 概念的双重性对未来人工智能系统的重要性。
Life-long learning and evolving associative memories in brain-inspired spiking neural networks
The paper argues that evolving associative memories (EAM), that are manifested in all biological systems and realised in the human brain through life-long learning (LLL), can be realised in brain-inspired computational architectures based on spiking neural networks (SNN). The paper points to the importance of the duality of the concepts of EAM and LLL for future AI systems.
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