【24h】

Deep IA-BI and Five Actions in Circling

机译:深入的IA-BI和盘旋五项动作

获取原文

摘要

Deep bidirectional Intelligence (BI) via YIng YAng (IA) system, or shortly Deep IA-BI, is featured by circling A-mapping and I-mapping (or shortly AI circling) that sequentially performs each of five actions. A basic foundation of IA-BI is bidirectional learning that makes the cascading of A-mapping and I-mapping (shortly A-I cascading) approximate an identical mapping, with a nature of layered, topology-preserved, and modularised development. One exemplar is Lrnser that improves autoencoder by incremental bidirectional layered development of cognition, featured by two dual natures DPN and DCW. Two typical IA-BI scenarios are further addressed. One considers bidirectional cognition and image thinking, together with a proposal that combines theories of Hubel-Wiesel's versus Chen's. The other considers bidirectional integration of cognition, knowledge accumulation, and abstract thinking for improving implementation of searching, optimising, and reasoning. Particularly, an IA-DSM scheme is proposed for solving a doubly stochastic matrix (DSM) featured combinatorial tasks such as travelling salesman problem, and also a Subtree driven reasoning scheme is proposed for improving production rule based reasoning. In addition, some remarks are made on relations of Deep IA-BI to Hubel and Wiesel theory, Sperry theory, and A5 problem solving paradigm.
机译:通过YIng YAng(IA)系统进行的深度双向智能(BI),或简称为Deep IA-BI,其特征是循环执行A映射和I映射(或简称AI循环),依次执行五个动作中的每个动作。 IA-BI的基本基础是双向学习,它使A映射和I映射的级联(简称A-I级联)近似为相同的映射,具有分层,拓扑保留和模块化开发的性质。一个例子是Lrnser,它通过增量双向认知分层发展来改进自动编码器,具有两个双重性质DPN和DCW。进一步讨论了两种典型的IA-BI方案。人们考虑了双向认知和图像思维,并结合了Hubel-Wiesel和Chen的理论。另一方考虑了认知,知识积累和抽象思维的双向集成,以改善搜索,优化和推理的实现。尤其是,提出了一种IA-DSM方案来解决具有双重组合特征的双重随机矩阵(DSM),例如旅行商问题,并且还提出了一种基于子树的推理方案,以改进基于生产规则的推理。此外,还对Deep IA-BI与Hubel和Wiesel理论,Sperry理论以及A5问题解决范例的关系作了一些评论。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号