TARTARUS AND FRACTAL GENE REGULATORY NETWORKS WITH INPUTS

P. Zahadat () and S. D. Katebi ()
Additional contact information
P. Zahadat: Department of Computer Science and Engineering, School of Engineering, Shiraz University, Shiraz, Iran
S. D. Katebi: Department of Computer Science and Engineering, School of Engineering, Shiraz University, Shiraz, Iran

Advances in Complex Systems (ACS), 2008, vol. 11, issue 06, pages 803-829

Abstract: Tartarus is a benchmark problem used to evaluate artificial intelligence techniques for solving problems in the field of non-Markovian agent motion planning. In this paper a fractal gene regulatory network with inputs is evolved to act as a virtual robot controller in the Tartarus environment. The proposed technique is compared and contrasted with other previously reported techniques and it is shown that the gene regulatory network that includes input information provides an excellent performance without using any explicit memory or environmental modeling. Detailed experimental studies are presented to illustrate the effectiveness and superiority of the proposed approach.

Keywords: Evolutionary computation; gene regulatory network; fractals; Tartarus; control (search for similar items in EconPapers)
Date: 2008

Downloads: (external link)
http://www.worldscinet.com/cgi-bin/details.cgi?type=pdf&id=pii:S0219525908001982 (application/pdf)
http://www.worldscinet.com/cgi-bin/details.cgi?typ ... ii:S0219525908001982 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: http://EconPapers.repec.org/RePEc:wsi:acsxxx:v:11:y:2008:i:06:p:803-829

Ordering information: This journal article can be ordered from

Access Statistics for this article

Advances in Complex Systems (ACS) is edited by Frank Schweitzer

More articles in Advances in Complex Systems (ACS) from World Scientific Publishing Co. Pte. Ltd.
Series data maintained by Tai Tone Lim ().