人脑进化中的微观计算

Ron Wallace Ph.D.
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引用次数: 3

摘要

当我们从认知模块的角度来看待人类的心理表现时,我们的物种在计算能力上表现出了显著的差异。简单的算法计算通常很难执行,而最优路线或“旅行推销员”︁问题(TSP)的复杂性要大得多,在日常基础上得到解决。有人认为,即使是“简单的”︁TSP实例也不是人类计算中纯粹的欧几里得问题,而是涉及情感、自主和认知约束。因此,它们需要一定程度的并行处理,这在宏观系统中是不可能在短时间内完成算法的。微观神经生物学模型强调神经元膜内激发原子的计算能力,作为经典连接主义方法的替代方案。系统的进化被看作是特定的自然选择压力驱使满意的计算向全局优化。考察了微观计算与意识本质的关系,并简要讨论了作为模拟研究基础的可能的数学模型。
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Micdroscopic computation in human brain evolution

When human psychological performance is viewed in terms of cognitive modules, our species displays remarkable differences in computational power. Algorithmically simple computations are generally difficult to perform, whereas optimal routing or „Traveling Salesman”︁ Problems (TSP) of far greater complexity are solved on an everyday basis. It is argued that even „simple”︁ instances of TSP are not purely Euclidian problems in human computations, but involve emotional, autonomic, and cognitive constraints. They therefore require a level of parallel processing not possible in a macroscopic system to complete the algorithm within a brief period of time. A microscopic neurobiological model emphasizing the computational power of excited atoms within the neuronal membrane is presented as an alternative to classical connectionist approaches. The evolution of the system is viewed in terms of specific natural selection pressures driving satisfying computations toward global optimization. The relationship of microscopic computation to the nature of consciousness is examined, and possible mathematical models as a basis for simulation studies are briefly discussed.

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