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Subymbolic AI

  • Subsymbolic AI (SSAI) aims to model intelligence empirically.

  • SSAI was inspired by biological systems: A model which imitates neural nets in the brain is the basis for the creation of artificial intelligence.

  • Neural nets consist of a network of
    neurons which have weighted connections
    with each other.

  • Early work by Rosenblatt (1962):
    the “Perceptron” [6]

  • Advantages of artificial neuronal nets:

    • Distributed representation

    • Representation and processing of fuzziness

    • Highly parallel and distributed action

    • Speed and fault-tolerance


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