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A Hybrid Connectionist Expert System for Spatial Inference and Analysis

In: Spatial Economic Science

Author

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  • Yee Leung

    (The Chinese University of Hong Kong)

Abstract

The major challenge in the design of intelligent spatial reasoning systems lies on our ability to build into a system mechanisms to memorize and use knowledge extracted from domain-specific experts, and to automatically acquire knowledge from voluminous but incomplete information through learning by examples. Such system can facilitate machine reasoning in a commonly encountered environment where knowledge, in terms of explicitly specified rules, and information, in the form of raw data, digitized maps or remotely sensed images, are mixed together. The situation is equivalent to human reasoning with previously taught or acquired knowledge that sits in our memories, and knowledge to be acquired by self-learning from our everyday experience.

Suggested Citation

  • Yee Leung, 2000. "A Hybrid Connectionist Expert System for Spatial Inference and Analysis," Advances in Spatial Science, in: Aura Reggiani (ed.), Spatial Economic Science, chapter 9, pages 149-187, Springer.
    • Handle: RePEc:spr:adspcp:978-3-642-59787-9_9
    DOI: 10.1007/978-3-642-59787-9_9
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