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A Genetic Algorithmic Approach to Automated Auction Mechanism Design

Jinzhong Niu and Simon Parsons. A Genetic Algorithmic Approach to Automated Auction Mechanism Design. In Proceedings of the 17th International Workshop on Agent-Mediated Electronic Commerce and Trading Agents Design and Analysis (AMEC/TADA), New York, NY, 2016.

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Abstract

In this paper, we present a genetic algorithmic approach to automated auction mechanism design in the context of CAT games. This is a follow-up to one piece of our prior work in the domain, the reinforcement learning-based grey-box approach, which was published in the AMEC 2010 workshop. Our experiments show that given the same search space the grey-box approach is able to produce better auction mechanisms than the genetic algorithmic approach. The comparison can also shed light on the design and evaluation of similar search solutions to other domain problems.

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BibTeX

@INPROCEEDINGS{niu-amectada2016-gamd,
  AUTHOR =       "Jinzhong Niu and Simon Parsons",
  TITLE =        "A Genetic Algorithmic Approach to Automated Auction Mechanism Design",
  BOOKTITLE =   amectada16,
  editor =       "Sofia Ceppi and Ioannis A. Vetsikas and Chen Hajaj and Esther David and Valentin Robu",
  YEAR =         "2016",
  address =      nyc,
  abstract = niu-amectada2016-gamd-abstract,
}

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