计算机工程与应用 ›› 2020, Vol. 56 ›› Issue (21): 170-175.DOI: 10.3778/j.issn.1002-8331.2004-0408

• 模式识别与人工智能 • 上一篇    下一篇

讨价还价博弈均衡出价策略的算法设计

徐齐利   

  1. 江西财经大学 经济学院,南昌 330013
  • 出版日期:2020-11-01 发布日期:2020-11-03

Algorithm Design of Equilibrium Bidding Strategy in Bargaining Game

XU Qili   

  1. School of Economics, Jiangxi University of Finance and Economics, Nanchang 330013, China
  • Online:2020-11-01 Published:2020-11-03

摘要:

在商业智能领域,为求解买卖双方讨价还价博弈的均衡出价策略,在逆向归纳法的基础上,开发出两个高效且实用的算法:基于逆向归纳过程,设计出迭代算法;基于逆向归纳结果,设计出递归算法。迭代算法是逆向归纳法的具体实现,而递归算法则并不拘泥于逆向归纳法。在智能电子商务的讨价还价实战中,分设司令部、参谋部、作战部等三个角色模块,给出应用该算法开发智能出价决策支持系统的初步设计思路。

关键词: 算法博弈论, 递归算法, 迭代算法, 讨价还价博弈, 逆向归纳法, 商业智能

Abstract:

In the field of business intelligence, in order to solve the equilibrium bidding strategy of bargaining game between the buyer and the seller, two efficient and practical algorithms are developed based on reverse induction. Based on the reverse induction process, an iterative algorithm is designed. Based on the results of reverse induction, a recursive algorithm is designed. Iterative algorithm is the concrete implementation of reverse induction, while recursive algorithm is not constrained by reverse induction. In the bargaining practice of intelligent e-commerce, there are three role modules:command, staff and operation department. The preliminary design idea of developing bidding intelligence decision support system with this algorithm is given.

Key words: algorithmic game theory, recursive algorithm, iterative algorithm, bargaining game, reverse induction, business intelligence