CPC G06F 9/5072 (2013.01) [G06F 17/10 (2013.01); G06F 18/217 (2023.01); G06N 20/00 (2019.01); H04L 41/0866 (2013.01)] | 20 Claims |
1. A method for experimenting with modifications to a computational environment within a distributed system, comprising:
identifying a machine learning model trained to predict outputs for a computational environment having a first set of characteristics based on an input provided to the computational environment;
determining a modified output produced by the computational environment having a second set of characteristics, the second set of characteristics including a characteristic that has been modified from the first set of characteristics;
applying the machine learning model to the computational environment having the second set of characteristics to determine a predicted output based on the first set of characteristics; and
comparing the modified output to the predicted output to generate an output indicating an effect of a modification of the characteristic of the second set of characteristics that is different from the first set of characteristics.
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