Abstract
We report on an investigation of the feasibility of using connectionist-nets of the Rumelhart semi-linear feedforward type for learning and exercising intelligent system control. Of particular interest is the ability of such nets to discover the basis for decision and control. Of great interest also is an unexpected finding that such nets automatically build up a great deal of redundancy within itself so that it has a certain holographic quality to it and its performance degrades gradually with internal damage.
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Pao, YH. Autonomous machine learning of effective control strategies with connectionist-net. J Intell Robot Syst 1, 35–53 (1988). https://doi.org/10.1007/BF00437319
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DOI: https://doi.org/10.1007/BF00437319