TRAINING REINFORCEMENT MACHINE LEARNING SYSTEMS

• Main Authors: ZHAO, Xuan, CAMPOS, Marcos de Moura, SHNAYDER, Victor, STORY, Ross Ian, TRAUT, Eric Philip
• Format: Patent
• Language: English
• Published: 28.10.2021
• Subjects: CALCULATING; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS; COMPUTING; COUNTING; ELECTRIC DIGITAL DATA PROCESSING; PHYSICS

A method of training a reinforcement machine learning computer system. The method comprises providing a machine-learning computer programming language including a pre-defined plurality of reinforcement machine learning criterion statements, and receiving a training specification authored in the machine-learning computer programming language. The training specification defines a plurality of training sub-goals with a corresponding plurality of the reinforcement machine learning criterion statements supported by the machine-learning computer programming language. The method further comprises computer translating the plurality of training sub-goals from the training specification into a shaped reward function configured to score a reinforcement machine learning model configuration with regard to the plurality of training sub-goals. The method further comprises running a training experiment with the reinforcement machine learning model configuration, scoring the reinforcement machine learning model in the training experiment with the shaped reward function, and adjusting the reinforcement machine learning model configuration based on the shaped reward function.