The abilities of neural networks to abstract and to use abstractions

E. Marjomaa
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Abstract

The representation of concrete objects in neural networks is one of the important research areas in cognitive modeling. In the present work, the problem of the degree of abstractness is briefly considered, and some central concepts involving the representation of abstract entities are discussed. The epistemological status of the ability to use abstractions is discussed, and a proposal concerning the use of 'functants' in modeling abstract entities is considered.<>
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神经网络抽象和使用抽象的能力
神经网络中具体对象的表征是认知建模的重要研究领域之一。在本工作中,简要地考虑了抽象程度的问题,并讨论了涉及抽象实体表示的一些中心概念。讨论了使用抽象的能力的认识论地位,并考虑了在抽象实体建模中使用“函子”的建议。
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Control of a robotic manipulating arm by a neural network simulation of the human cerebral and cerebellar cortical processes Neural network training using homotopy continuation methods A learning scheme of neural networks which improves accuracy and speed of convergence using redundant and diversified network structures The abilities of neural networks to abstract and to use abstractions Backpropagation based on the logarithmic error function and elimination of local minima
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