类大脑突发空间处理

J. Weng, M. Luciw
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引用次数: 16

摘要

这是一篇关于类脑信息处理空间方面的理论、建模和算法论文,采用发育网络(DN)模型建模。新的大脑结构允许外部环境(包括教师)通过发展与封闭大脑的感觉端和运动端相互作用。它不允许人类程序员手工挑选额外的身体概念,也不允许在大脑中手工制作概念边界。从数学上讲,大脑的空间处理通过网络更新进行实时映射,其中所有内容都来自经验。大脑利用其有限的资源,通过经验做得越来越好。一个新的原理是,效应端是概念学习和抽象的中枢。效应端也作为输入端,感觉端也作为输出端。作为DN的具体体现,Where-What网络(WWNs)呈现出三个主要的功能创新——新概念抽象、作为紧急目标的概念和目标导向感知。WWN系列似乎是第一个通用的紧急系统,用于检测和识别复杂背景下的多个物体。在其他机制中,最重要的新机制是通用的自上而下的关注。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Brain-Like Emergent Spatial Processing
This is a theoretical, modeling, and algorithmic paper about the spatial aspect of brain-like information processing, modeled by the developmental network (DN) model. The new brain architecture allows the external environment (including teachers) to interact with the sensory ends and the motor ends of the skull-closed brain through development. It does not allow the human programmer to hand-pick extra-body concepts or to handcraft the concept boundaries inside the brain . Mathematically, the brain spatial processing performs real-time mapping from to , through network updates, where the contents of all emerge from experience. Using its limited resource, the brain does increasingly better through experience. A new principle is that the effector ends serve as hubs for concept learning and abstraction. The effector ends serve also as input and the sensory ends serve also as output. As DN embodiments, the Where-What Networks (WWNs) present three major function novelties-new concept abstraction, concept as emergent goals, and goal-directed perception. The WWN series appears to be the first general purpose emergent systems for detecting and recognizing multiple objects in complex backgrounds. Among others, the most significant new mechanism is general-purpose top-down attention.
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来源期刊
IEEE Transactions on Autonomous Mental Development
IEEE Transactions on Autonomous Mental Development COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-ROBOTICS
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