Abstract—In this article we are trying to present some algorithms and strategies in order to improve the rescue simulation and decrease the number of damages and pains that happens in the rescue simulation environment. Since the activities of an agent can have a deserving effect on efficiency, so it should be done by various things, such as information that any agent can obtain from surrounding environment, information that can be obtained from communication with homogeneous agents and order them. If there is no such information, we are trying to use machine learning and cooperation without communication strategies. In our study, cooperation and path planning have main role.
Index Terms—Rescue simulation, algorithm, RoboCup, artificial intelligence.
Abbas Khosravi and Mohammad Kazem Farhadipour are with the Computer Engineering Department, University of Payam Noor, Shiraz, Iran (e-mail: Khosravi1356@Yahoo.com, Kazem_Farhadipour@Yahoo.com). Seyed Mojtaba Hosseinifar is with the Industry Engineering Department, University of Payam Noor, Shiraz, Iran (e-mail: Hoseinifar.m@Gmail.com). Najme Roozmand is with the Psychology Department, University of Payam Noor, Shiraz, Iran (e-mail: Roozmandn@Yahoo.com).
Cite:Abbas Khosravi, Mohammad Kazem Farhadipour, Seyed Mojtaba Hosseinifar, and Najme Roozmand, "RoboGenius Team Description Paper Review and Develop AI Algorithms and Decision Making in Rescue Simulation Environment," International Journal of Machine Learning and Computing vol.3, no. 4, pp. 365-368, 2013.