Developing adaptive auction mechanisms

ABSTRACT

Mechanism design has traditionally been a largely analytic process, relying on assumptions such as fully rational bidders. In practice, however, these assumptions may not hold, making bidder behavior difficult to model and complicating the design process. To address this issue, we propose a different approach to mechanism design. Instead of relying on analytic methods that require specific assumptions about bidders, our approach is to create a self-adapting mechanism that adjusts auction parameters in response to past auction results. In this paper, we describe our approach and then present an example of its implementation to illustrate its efficacy.

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INDEX TERMS

Primary Classification:
  K. Computing Milieux
  K.4 COMPUTERS AND SOCIETY
      K.4.4 Electronic Commerce

Additional Classification:
  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
      I.2.1 Applications and Expert Systems
          Subjects: Office automation
      I.2.8 Problem Solving, Control Methods, and Search

  K. Computing Milieux
  K.4 COMPUTERS AND SOCIETY
      K.4.3 Organizational Impacts
          Subjects: Automation

General Terms:
Design, Economics, Performance, Theory

Keywords:
algorithms, auctions, economics, machine learning