On domination game analysis for microeconomic data mining

  • Authors:

  • Zhenjie Zhang;Laks V. S. Lakshmanan;Anthony K. H. Tung

  • Affiliations:

  • National University of Singapore, Singapore;University of British Columbia, Vancouver, B.C., Canada;National University of Singapore, Singapore

  • Venue:
  • ACM Transactions on Knowledge Discovery from Data (TKDD)
  • Year:
  • 2009

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Abstract

Game theory is a powerful tool for analyzing the competitions among manufacturers in a market. In this article, we present a study on combining game theory and data mining by introducing the concept of domination game analysis. We present a multidimensional market model, where every dimension represents one attribute of a commodity. Every product or customer is represented by a point in the multidimensional space, and a product is said to “dominate” a customer if all of its attributes can satisfy the requirements of the customer. The expected market share of a product is measured by the expected number of the buyers in the customers, all of which are equally likely to buy any product dominating him. A Nash equilibrium is a configuration of the products achieving stable expected market shares for all products. We prove that Nash equilibrium in such a model can be computed in polynomial time if every manufacturer tries to modify its product in a round robin manner. To further improve the efficiency of the computation, we also design two algorithms for the manufacturers to efficiently find their best response to other products in the market.