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Morphognosis: the shape of knowledge in space and time

机译:形态化:空间和时间的知识形状

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Artificial intelligence research to a great degree focuses on the brain and behaviors that the brain generates. But the brain, an extremely complex structure resulting from millions of years of evolution, can be viewed as a solution to problems posed by an environment existing in space and time. The environment generates signals that produce sensory events within an organism. Building an internal spatial and temporal model of the environment allows an organism to navigate and manipulate the environment. Higher intelligence might be the ability to process information coming from a larger extent of space-time. In keeping with nature's penchant for extending rather than replacing, the purpose of the mammalian neocortex might then be to record events from distant reaches of space and time and render them, as though yet near and present, to the older, deeper brain whose instinctual roles have changed little over eons. Here this notion is embodied in a model called morphognosis (morpho = shape and gnosis = knowledge). Its basic structure is a pyramid of event recordings called a morphognostic. At the apex of the pyramid are the most recent and nearby events. Receding from the apex are less recent and possibly more distant events. A morphognostic can thus be viewed as a structure of progressively larger chunks of space-time knowledge. A set of morphognostics forms long-term memories that are learned by exposure to the environment. A cellular automaton is used as the platform to investigate the morphognosis model, using a simulated organism that learns to forage in its world for food, build a nest, and play the game of Pong.
机译:人工智能研究到大程度的重点是大脑产生的大脑和行为。但是,由于数百万年的演化产生的大脑,这是一个极其复杂的结构,可以被视为在空间和时间存在的环境构成的问题的解决方案。环境生成产生在生物体内产生感官事件的信号。建立环境的内部空间和时间模型允许有机体导航和操纵环境。更高的智能可能是处理来自更大程度的时空信息的信息。在与大自然的倾斜而不是替代的情况下,哺乳动物Neocortex的目的可能是从遥远的空间和时间记录事件,并使它们达到较旧的,更深入的大脑,其本能作用已经变得少于eons。这里,这种概念体现在一个名为性能(Morpho = Shape和Gnosis =知识)的模型中。它的基本结构是事件记录的金字塔称为形态学。在金字塔的顶点是最近和附近的活动。从顶点退出的是最近且可能更遥远的事件。因此,形态学可以被视为逐步更大的时空知识块的结构。一系列的形态学,形成了通过接触环境来学习的长期记忆。使用蜂窝自动机作为调查形态诊断模型的平台,使用模拟生物,这些生物在其世界中觅食,建造巢穴和乒乓球比赛。

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