Research on Bargaining Algorithm of Unmanned Vending Machine Based on Game Strategy

Abstract

Traditional unmanned vending machines currently do not have the function of bargaining, and cannot provide consumers with personalized bargaining intelligent services. Based on the psychological benefits of users being more inclined to buy discounted goods, the study aims to introduce the bargaining function to unmanned vending machines. Use bargaining to stimulate paid conversions of purchases. This is similar to a business scheme that uses discounts on goods or issues coupons to stimulate customers to pay. This study makes up for the gap in the bargaining function of unmanned vending machines, which is of great significance. Based on the game strategy, this study establishes a set of algorithmic models for unmanned vending machine bargaining. The algorithmic model applies five different sub-algorithms. When the unmanned vending machine bargains with the customer, the algorithm model only randomly selects one of the sub-algorithm models within a fixed period of time. Next, the selected sub-algorithm performs the commodity bargaining game operation and outputs the game result. Therefore, the algorithm is applied to unmanned vending machines, adding personalized bargaining functions. It meets the bargaining expectations and purchase needs of different customers. In a limited space, the article focuses on the implementation of mathematical principles of unmanned vending machine bargaining algorithm based on game strategy. The study describes the interaction between the two sides of the game. In this study, simulation experiments are carried out to verify the accuracy of the algorithm model by analyzing a series of parameters.