Publications / 2000 Proceedings of the 17th ISARC, Taipei, Taiwan

A Bidding Model Combined Game Theory and AI Paradigms

Tao-Sheng Wu, Ming-Teh Wang
Pages 1-5 (2000 Proceedings of the 17th ISARC, Taipei, Taiwan, ISBN 9789570266986, ISSN 2413-5844)
Abstract:

There are many similar attributes in the behaviors of auction and construction bidding. As studied in economics, it has been widely discussed in game theory. However, game theorists may not be familiar with the subtle differences between auction and construction bidding. As an analytical framework, game theory has the merits of reducing the complication of competitive bidding, but it is still difficult to pursue answers with statistics. Since artificial neural network techniques have been frequently applied to solve ill-structured problems in many areas, they may also be applied to predict tender prices on construction bidding. To do such a prediction, this paper utilizes three methods: statistic, Neural network, and neuro-fuzzy, to compare their results. This study will address the advantages in using artificial intelligence methods.

Keywords: completive bidding model, neural network, fuzzy sets, game theory