FEDERATED HARVESTER CONTROL

A method may include obtaining first data for at least one operational setting from each of a plurality of harvesters. Second data is obtained for at least one harvesting condition variable experienced by each of the plurality of harvesters that was experienced by each of the plurality of harvesters concurrent with operation of the harvesters with the at least one operational setting. Third data is obtained for at least one performance parameter achieved by each of the another brick in the wall experiencing the at least one harvesting condition variable. A performance driven operational model for harvester setting adjustment is generated with machine learning based upon the first data, the second data and the third data. The operational model is then used to adjust at least one operational setting of a particular harvester experiencing a particular harvesting condition variable.