Abstract
In this paper, two neural network mechanisms for synthesis of solutions in non-conflict cases in distributed expert systems (DESs) are proposed. The ideas are: inputs of the neural network are different solutions for the same problem from different expert systems in DESs; outputs of the neural network are the final solutions for the problem after combining different solutions which should be the same as the human experts' final solutions. The first point is to set up the architecture of the neural network and train the neural network by adjusting weights of links to match the outputs of the neural network against the human experts' solutions for all patterns. The second point is that the neural network mechanism proposed in this paper can accommodate the variable number of inputs and outputs without changing neural network architecture.
This research was supported by a large grant from the Australian Research Council (A49530850).
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© 1996 Springer-Verlag Berlin Heidelberg
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Zhang, M., Zhang, C. (1996). Neural network strategies for solving synthesis problems in non-conflict cases in distributed expert systems. In: Zhang, C., Lukose, D. (eds) Distributed Artificial Intelligence Architecture and Modelling. DAI 1995. Lecture Notes in Computer Science, vol 1087. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-61314-5_29
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DOI: https://doi.org/10.1007/3-540-61314-5_29
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