Differences and commonalities between connectionism and symbolicism

  • Authors:

  • Shoujue Wang;Yangyang Liu

  • Affiliations:

  • Laboratory of Artificial Neural Networks, Institute of Semiconductors, Chinese academy of Sciences, Beijing, China;Laboratory of Artificial Neural Networks, Institute of Semiconductors, Chinese academy of Sciences, Beijing, China

  • Venue:
  • ISNN'05 Proceedings of the Second international conference on Advances in Neural Networks - Volume Part I
  • Year:
  • 2005

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Abstract

The differences between connectionism and symbolicism in artificial intelligence (AI) are illustrated on several aspects in details firstly; then after conceptually decision factors of connectionism are proposed, the commonalities between connectionism and symbolicism are tested to make sure, by some quite typical logic mathematics operation examples such as “parity”; At last, neuron structures are expanded by modifying neuron weights and thresholds in artificial neural networks through adopting high dimensional space geometry cognition, which give more overall development space, and embodied further both commonalities.