GTPA: A Generative Model For Online Mentor-Apprentice Networks

Authors

  • Muhammad Ahmad University of Minnesota
  • David Huffakar University of Michigan
  • Jing Wang Northwestern University
  • Jeff Treem Northwestern University
  • Marshall Poole University of Illinois - Urbana-Champaign
  • Jaideep Srivastava University of Minnesota

DOI:

https://doi.org/10.1609/aaai.v24i1.7506

Keywords:

Generative Models, Mentoring Networks, Social Networks

Abstract

There is a large body of work on the evolution of graphs in various domains, which shows that many real graphs evolve in a similar manner. In this paper we study a novel type of network formed by mentor-apprentice relationships in a massively multiplayer online role playing game. We observe that some of the static and dynamic laws which have been observed in many other real world networks are not observed in this network. Consequently well known graph generators like Preferential Attachment, Forest Fire, Butterfly, RTM, etc., cannot be applied to such mentoring networks. We propose a novel generative model to generate networks with the characteristics of mentoring networks.

Downloads

Published

2010-07-05

How to Cite

Ahmad, M., Huffakar, D., Wang, J., Treem, J., Poole, M., & Srivastava, J. (2010). GTPA: A Generative Model For Online Mentor-Apprentice Networks. Proceedings of the AAAI Conference on Artificial Intelligence, 24(1), 1294-1299. https://doi.org/10.1609/aaai.v24i1.7506

Issue

Vol. 24 No. 1 (2010): Twenty-Fourth AAAI Conference on Artificial Intelligence

Section

AAAI Technical Track: AI and the Web