Nemesis Team Description 2009

In our study, we tried to develop our teams in such a way that machine learning techniques and advanced artificial intelligence tools have the main role in improving skills and increasing team performance. We consider soccer simulation platform as an uncertain and dynamic environment, so we develop learning algorithms according to this important feature and agent's partial observability.

[1]  Tucker R. Balch,et al.  Distributed sensor fusion for object position estimation by multi-robot systems , 2001, Proceedings 2001 ICRA. IEEE International Conference on Robotics and Automation (Cat. No.01CH37164).

[2]  OFF-CAMPUS HOUSING Brigham Young University , 2004 .

[3]  Brian S. Stensrud,et al.  Context-Based Reasoning: A Revised Specification , 2004, FLAIRS.

[4]  Kagan Tumer,et al.  Team Formation in Partially Observable Multi-Agent Systems , 2004 .

[5]  Ching-Hung Lee,et al.  Identification and control of dynamic systems using recurrent fuzzy neural networks , 2000, IEEE Trans. Fuzzy Syst..

[6]  Kagan Tumer,et al.  Optimal Payoff Functions for Members of Collectives , 2001, Adv. Complex Syst..

[7]  Mohammad Bagher Menhaj,et al.  Transition from particle swarm optimization to individual particle optimization , 2009, 2009 IEEE Control Applications, (CCA) & Intelligent Control, (ISIC).

[8]  Leslie Pack Kaelbling,et al.  Planning and Acting in Partially Observable Stochastic Domains , 1998, Artif. Intell..

[9]  Peyman Yadmellat,et al.  A Hybrid Algorithm for Training Recurrent Fuzzy Neural Network , 2008, Artificial Intelligence and Pattern Recognition.