TECHNIQUE FOR CONFIGURING A REINFORCEMENT LEARNING AGENT

• Main Authors: TERRA, Ahmad Ishtar, INAM, Rafia, RIAZ, Hassam, KATTEPUR, Ajay, HATA, Alberto, SOMANAHALLI KRISHNA MURTHY, Prayag Gowgi
• Format: Patent
• Language: English
• Published: 13.06.2024
• Subjects: CALCULATING; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS; COMPUTING; COUNTING; PHYSICS

A technique for configuring a reinforcement learning agent to perform a task using a reward structure derived from a task-specific definition of metric importances is disclosed. A method is performed by a computing unit executing a configurator component and includes obtaining a definition of metric importances specifying, for a plurality of performance-related metrics associated with the task, pairwise importance values each indicating a relative importance of one metric with respect to another metric of the plurality of performance-related metrics for the task, deriving a reward structure from the definition of metric importances, the reward structure defining, for each of the plurality of performance-related metrics, a reward to be attributed to an action taken by the reinforcement learning agent that yields a positive outcome in the respective performance-related metric, and configuring the reinforcement learning agent to employ the derived reward structure when performing the task.