Technique for configuring a reinforcement learning agent

Abstract

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.

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