The invention provides an unmanned
market management method and
system based on
reinforcement learning, and the method comprises the steps: carrying out the
source data collection of commodities sold in an unmanned market, generating a commodity source
fingerprint set in combination with a chaos
algorithm and a verifiable
delay function, carrying out the game analysis of the commodity source
fingerprint set based on multi-agent
reinforcement learning, and carrying out the game analysis of the commodity source
fingerprint set. The method comprises the following steps: dynamically pricing each commodity in an unmanned mart, generating a corresponding
colored glaze code, constructing a dual-mode transaction platform, carrying out transaction on the dual-mode transaction platform by a user, generating a transaction order, carrying out
traceability verification by the user according to the
colored glaze code of the commodity in the transaction order, generating a
traceability verification result, generating a transaction
record data set based on the
traceability verification result, and storing the transaction
record data set in the unmanned mart. According to the method, the unmanned market is analyzed, an unmanned
market management log is generated in combination with a transaction
record data set, unmanned market feedback optimization is carried out based on the unmanned
market management log, efficient and credible
butt joint of supply and demand is realized, and the problem that supply resources of high-quality agricultural products are idle and market demands are mismatched is avoided.