Patent ID: 11887138
Assignee: DAISY INTELLIGENCE CORPORATION
Field: IT methods for management (Electrical engineering)
Classification: CPC G | IPC G

Claim 7:
8. A system for generating a retail price model and a selected control policy, the electronic retail price model and the selected control policy for generating an electronic retail price plan for retail operations performed within an enterprise network comprising a plurality of distributed computing devices, the plurality of distributed computing devices comprising a plurality of point-of-sale devices and a plurality of enterprise servers, the plurality of distributed computing devices in network communication, comprising:
a memory, the memory comprising:
transaction data from the plurality of point-of-sale devices, the transaction data defined as a time series including a plurality of transaction data items corresponding to one or more previous time periods, the plurality of transaction data items comprising at least one of price data, product data, and customer data;
a short-term memory storing one or more simulated system states and one or more simulated system rewards;
a long-term memory storing a plurality of long-term sensor data; and
an intelligent agent module comprising a simulation component;

a processor in communication with the memory, the processor configured to:
determine transformed transaction data including a power spectrum of the time series transaction data, the power spectrum comprising a vertical axis of amplitude and a horizontal axis of frequency and the transformed transaction data indicating gross or aberrant trends in the transaction data by,
determining one or more transaction values of the transaction data for each of the two or more previous time periods,

determine one or more features from the transformed transaction data;
determine one or more actionable features from the one or more features;
generate an electronic retail price model from the one or more actionable features;
store the electronic retail price model in the memory;
select a selected control policy for the retail promotional model, by,
executing a reward function based on the retail data for each time period in the one or more time periods; and
selecting one or more coefficients that maximize the output of the reward function for the one or more time periods,

store the selected control policy in the memory;
simulate, using the simulation component, a plurality of simulated pricing decisions based on the electronic retail price model and the selected control policy to update the one or more simulated system states and the one or more simulated system rewards;
receive, the updated one or more simulated system states and the updated one or more simulated system rewards from the simulation component;
receive, a measured state of an operational system and a measured reward of the operational system;
correct, at the intelligent agent, the one or more simulated system states based on the updated one or more simulated system states, the measured state of the operational system, the updated one or more simulated system rewards and the measured reward of the operational system; and
determine the electronic retail price plan based on the one or more simulated system states and the one or more simulated system rewards.