Adaptive system of heterogeneous multi-agent investors in an artificial evolutionary double auction market

Chi Xu, Xiaoyu Zhao, Zheru Chi

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

2 Citations (Scopus)

Abstract

In this paper, an adaptive system is proposed which attempts to combine together the approaches of studies of historical data and researches of multi-agent artificial market by evolving a double auction market model with diversity of different traders. The purpose of this research is to construct an artificial market which is more close to realistic one and more practical for future researches. The model with heterogeneous agents and the environment with which agents and market interact is complicated but controllable by data mining the optimal proportion of the different agents at the input to the market that generates an output which can fit historical data curve. The simulation results suggest that the system performance is close to the expecting values in the testing with adequate training in advance.
Original languageEnglish
Title of host publicationAdvances in Swarm Intelligence - First International Conference, ICSI 2010, Proceedings
Pages715-722
Number of pages8
EditionPART 1
DOIs
Publication statusPublished - 21 Jul 2010
Event1st International Conference on Advances in Swarm Intelligence, ICSI 2010 - Beijing, China
Duration: 12 Jun 201015 Jun 2010

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 1
Volume6145 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference1st International Conference on Advances in Swarm Intelligence, ICSI 2010
CountryChina
CityBeijing
Period12/06/1015/06/10

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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