Enhancing package formation in a food packaging system based on reinforcement learning

A food packaging machine comprising:

• a plurality of local sub-systems configured to produce individual packages filled with one or more food products;
• a memory;
• and
• a processor,
• wherein the memory stores instructions that, when executed by the processor, cause the processor to perform a method comprising:
• receiving one or more remote variable values indicating measurements by the food packaging machine of one or more physical parameters for one or remote sub-systems;
• receiving one or more local variable values indicating measurements by the food packaging machine of one or more physical parameters for a local sub-system of the plurality of local sub-systems;
• determining one or more control parameter values for the local sub-system, by processing the local variable values using a a local control model;
• updating the one or more control parameter values for the local sub-system, by processing the remote variable values using a reinforcement learning model;
• adjusting one or more control parameters of the local sub-system in accordance with the determined control parameter values;
• and
• controlling a formation of individual packages by the food packaging machine in accordance with the adjusted one or more control parameters.