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- W2218212812 abstract "The paper describes a radical modification to the well-known BOXES methodology. Learning with the BOXES paradigm is slow and capricious, and it is proposed that the insertion of voting logic will accelerate and improve the process, particularly in the case of poorly defined systems. Advisor states are selected by a modified BOXES state quantization algorithm, rated for positional strength and made accountable, statistically speaking, for their contribution to the performance of the system, by a new post-processing algorithm. In the spirit of the conference theme, a reference is made to the possible application of the method to the control of a municipal trash-tosteam plant." @default.
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- W2218212812 title "Super-boxes - An Accountable AdvisorSystem" @default.
- W2218212812 doi "https://doi.org/10.2495/aieng930352" @default.
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