Dynamic Inventory Segmentation with Predicted Prediction Time Window

A machine learning system for dynamically segmenting inventory, comprising:

• a memory having instructions therein;
• and
• at least one processor in communication with the memory, wherein the at least one processor is configured to execute the instructions to:
• determine, using a reinforcement learning agent, based at least in part on first inventory data corresponding to at least a portion of a first prediction time window for the reinforcement learning agent, a second prediction time window for the reinforcement learning agent;
• segment a first supply of inventory, using the reinforcement learning agent, based at least in part on the second prediction time window and at least a portion of the first inventory data;
• determine, using the reinforcement learning agent, based at least in part on second inventory data corresponding to at least a portion of the second prediction time window, a third prediction time window for the reinforcement learning agent;
• and
• segment a second supply of inventory, using the reinforcement learning agent, based at least in part on the third prediction time window and at least a portion of the second inventory data.

A computer program product for machine learning dynamic inventory segmentation, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by at least one processor to cause the at least one processor to:

• determine, using a reinforcement learning agent, based at least in part on first inventory data corresponding to at least a portion of a first prediction time window for the reinforcement learning agent, a second prediction time window for the reinforcement learning agent;
• segment a first supply of inventory, using the reinforcement learning agent, based at least in part on the second prediction time window and at least a portion of the first inventory data;
• determine, using the reinforcement learning agent, based at least in part on second inventory data corresponding to at least a portion of the second prediction time window, a third prediction time window for the reinforcement learning agent;
• and
• segment a second supply of inventory, using the reinforcement learning agent, based at least in part on the third prediction time window and at least a portion of the second inventory data.