Systems for constructing hierarchical training data sets for use with machine-learning and related methods therefor

16) A method being implemented via execution of computer instructions configured to run at one or more processors and configured to be stored at one or more non-transitory memory storage devices, the method comprising:

• constructing a hierarchical training data set;
• and
• applying machine-learning to the hierarchical training data set to determine at least one first optimal control input value of a first control input for a first controlled device of multiple controlled devices;
• wherein:
• constructing the hierarchical training data set comprises:
• receiving a first training data set, the first training data set consisting of first training data having been generated by the first controlled device;
• determining that the first training data set is inadequate to fully form the hierarchical training data set;
• receiving a second training data set, the second training data set consisting of second training data having been generated by at least two controlled devices of the multiple controlled devices, and the at least two controlled devices comprising the first controlled device;
• and
• supplementing the first training data set with the second training data set to form the hierarchical training data set.

23) A system comprising:

• one or more processors;
• and
• one or more non-transitory memory storage devices storing computer instructions configured to run on the one or more processors and perform:
• constructing a hierarchical training data set;
• and
• applying machine-learning to the hierarchical training data set to determine at least one first optimal control input value of a first control input for a first controlled device of multiple controlled devices;
• and
• applying machine-learning to the hierarchical training data set to determine at least one second optimal control input value of a second control input for the first controlled device of the multiple controlled devices;
• wherein:
• the multiple controlled devices comprise the at least two controlled devices and at least one other controlled device;
• and
• constructing the hierarchical training data set comprises:
• receiving a first training data set, the first training data set consisting of first training data having been generated by the first controlled device;
• determining that the first training data set is inadequate to fully form the hierarchical training data set;
• receiving a second training data set, the second training data set consisting of second training data having been generated by at least two controlled devices of the multiple controlled devices, and the at least two controlled devices comprising the first controlled device;
• supplementing the first training data set with the second training data set to form the hierarchical training data set;
• determining that the first training data set and the second training data set are inadequate to fully form the hierarchical training data set;
• receiving a third training data set, the third training data set consisting of third training data having been generated by all of the multiple controlled devices;
• determining that the first training data set, the second training data set, and the third training data set are inadequate to fully form the hierarchical training data set;
• receiving a fourth training data set, the fourth training data set consisting of fourth training data having been simulated for the multiple controlled devices;
• and
• supplementing the first training data set, the second training data set, and the third training data set with the fourth training data set to form the hierarchical training data set.