Reinforcement learning control of vehicle systems

A system comprising:

• a first system associated with a first vehicle;
• a second system associated with a second vehicle;
• and
• one or more memory devices configured to store instructions thereon that, when executed by one or more processors, cause the one or more processors to:
• store a policy in the one or more memory devices;
• receive information regarding operation of the first system and information regarding operation of the second system;
• input the information regarding operation of the first system and the second system into the policy;
• determine an output of the policy based on the input of the information regarding operation of the first system and the second system;
• and
• control operation of the first system according to the output.

A method comprising:

• storing, by one or more processors in one or more memory devices, a policy;
• receiving, by the one or more processors, information regarding a first vehicle system and a second vehicle system;
• inputting, by the one or more processors, the received information into the policy;
• determining, by the one or more processors, an output of the policy based on the inputted information;
• controlling, by the one or more processors, operation of the first vehicle system according to the output;
• providing, by the one or more processors, a reward signal or a penalty signal in response to information received after controlling operation of the first vehicle system according to the output;
• updating, by the one or more processors, the policy based on receipt of the reward signal or the penalty signal;
• and
• controlling, by the one or more processors, operation of at least one of the first vehicle system or the second vehicle system using the updated policy.