Testing of Real-Time Embedded Systems (RTES) is in many ways challenging. Thousands of test cases can be potentially executed on industrial RTES. Given the magnitude of testing at the system level, only a fully automated approach can really scale up to test industrial RTES. The performance and usefulness of Real Time Autonomous Embedded Systems (RTAES) can be enhanced by providing them with Artificial Intelligence (AI). Since embedded systems are generally constrained by multiple factors (e.g., power consumption, processing speed, memory, etc.), full-fledged AI implementation is not feasible for most RTAES designs.