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Towards a new computational model of mind and theory of the cerebral neocortex: Will Valentino help SAM to find a mind like ours for TARSAN ?

机译:迈向大脑新皮层的思维和理论的新计算模型:Valentino是否会帮助SAM为TARSAN找到像我们这样的思维?

摘要

Building machines like us, machines with minds like ours, has been a goalof Artificial Intelligence (AI) since its inception. Unfortunately, the greaterpart of research in traditional AI has ignored work in neuroscience and thephilosophy of mind. At the same time, traditional AI systems havegenerally been brittle, difficult to engineer and, most importantly, havelacked the same nature and essential properties as human cognitivesystems. The objectives of this research are: 1) to justify and motivateresearch in computational neuroscience as an alternative path tounderstanding and engineering human cognitive systems, 2) to construct asoftware system for “wiring” and simulating brains at the functional (ornear-neural) level, and 3) to obtain a better understanding of highercognitive function based on a study of the neuroanatomy andneurophysiology, and current models and theories, of the cerebralneocortex. The thesis embraces a multi-disciplinary approach combiningwork in the philosophy of mind, neuroscience, and computer science.Although preferring to reverse engineer the brain (rather than engineering acognitive system independently, as generally done in AI), this work doesattempt to balance this analysis with the synthesis of systems and theories.Results include a resolution of the dispute between the classicalcognitivists and connectionists about the nature of mind which argues thatto build cognitive systems with minds like ours requires they be built at thefunctional (or near neural) level, a justification for the analysis of the brainto guide the construction of human-like cognitive systems, the constructionof a novel software system for “wiring” and simulating cognitive systemsat the functional (or near-neural) level, a review and analysis of thestructure and function of the cerebral neocortex, a review and analysis ofmodels and theories of, and systems inspired by, the cerebral neocortex,the preliminary aspects of a new architecture and learning strategy (whichrepresents preliminary steps towards a new theory) for the cerebralneocortex, and the construction of a powerful robot and environmentsimulation system. This thesis has taken initial steps to demonstrate that anappropriate simulation system, theory based on the human brain, and testenvironment can be constructed, that may indeed make it possible to buildcognitive systems with the same nature and essential properties as ours.An alternative AI may succeed.
机译:自成立以来,制造像我们这样的机器,怀着我们这样的思维的机器一直是人工智能(AI)的目标。不幸的是,传统AI的大部分研究都忽略了神经科学和心智哲学方面的工作。同时,传统的AI系统通常很脆弱,难以工程设计,最重要的是,它缺乏与人类认知系统相同的性质和基本特性。这项研究的目的是:1)证明并激发对计算神经科学的研究,作为理解和工程化人类认知系统的另一种途径; 2)构建用于在功能(ornear-neural)级别“布线”和模拟大脑的软件系统, (3)通过对神经解剖学和神经生理学以及当前大脑皮层模型和理论的研究,可以更好地理解高认知功能。论文采用了一种多学科的方法,将心智,神经科学和计算机科学的工作相结合。尽管更喜欢对大脑进行逆向工程(而不是像AI中通常那样独立地对认知系统进行工程设计),但这项工作确实试图平衡这种分析结果包括解决了古典认知主义者和连接主义者之间关于精神本质的争论,该争论认为,要用我们这样的思想来构建认知系统,就需要在功能(或接近神经)水平上建立这种体系,这是有道理的。为了分析大脑以指导类似人的认知系统的构建,用于在功能(或近神经)水平上“连接”和模拟认知系统的新型软件系统的构建,对结构和功能的回顾和分析大脑新皮层,对大脑神经网络的模型和理论以及受其启发的系统的回顾和分析大脑皮层,大脑皮层的新架构和学习策略(代表着迈向新理论的初步步骤)的初步方面,以及功能强大的机器人和环境模拟系统的构建。本论文采取了初步步骤来证明可以构建适当的仿真系统,基于人脑的理论和测试环境,这确实有可能使构建具有与我们相同的本质和基本特性的认知系统成为可能。 。

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