Abstract: An embodiment relates to a system of a vehicle comprising a first vehicle ecosystem module comprising a first communication system and a first vehicle ecosystem unit comprising a local environment matrix, and a global governance module that is internal or external to the system, wherein the global governance module comprises a learning agent and a second communication system comprising a protocol unit, wherein the learning agent is configured to learn continuously and update rules for an outcome of the first vehicle ecosystem module when power in the vehicle is turned on, wherein the system is configured for autonomous communication between the first vehicle ecosystem unit and a second vehicle ecosystem unit, wherein the second vehicle ecosystem unit is either internal or external to the system.

Abstract: An embodiment relates to a system of a vehicle comprising a first vehicle ecosystem module comprising a first communication system and a first vehicle ecosystem unit comprising a local environment matrix, and a global governance module that is internal or external to the system, wherein the global governance module comprises a learning agent and a second communication system comprising a protocol unit, wherein the learning agent is configured to learn continuously and update rules for an outcome of the first vehicle ecosystem module when power in the vehicle is turned on, wherein the system is configured for autonomous communication between the first vehicle ecosystem unit and a second vehicle ecosystem unit, wherein the second vehicle ecosystem unit is either internal or external to the system.

Abstract: An embodiment relates to a system of a vehicle comprising a first vehicle ecosystem module comprising a first communication system and a first vehicle ecosystem unit comprising a local environment matrix, and a global governance module that is internal or external to the system, wherein the global governance module comprises a learning agent and a second communication system comprising a protocol unit, wherein the learning agent is configured to learn continuously and update rules for an outcome of the first vehicle ecosystem module when power in the vehicle is turned on, wherein the system is configured for autonomous communication between the first vehicle ecosystem unit and a second vehicle ecosystem unit, wherein the second vehicle ecosystem unit is either internal or external to the system.

Abstract: Systems, devices, computer-implemented methods, and/or computer program products that facilitate modifying electronic control system behavior using distributed and/or federated machine intelligence. In one example, a system can comprise a process that executes computer executable components stored in memory. The computer executable components can comprise a model manager, a control component, and a learning component. The model manager can construct a trainable model using a pre-trained template model that is received via an in-vehicle network from a domain chief. The control component can dynamically vary a control parameter of a vehicle functional unit using the pre-trained template model to calibrate an output of the vehicle functional unit. The learning component can modify the trainable model based on observational data of the vehicle functional unit.