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RoboCupRescue system and Arian: a flexible infrastructure for multi-agent research and education

One of the main requisites for multi agent researchers is a multi-purpose infrastructure that enables them to create, test and evaluate protocols, methods and algorithms. RoboCupRescue simulation environment is a flexible and configurable environment that can fill this gap. With changes in its configuration files, it will gain different features, so different methods can be designed, implemented, and tested. This environment is actually suitable for most multi-agent research issues such as cooperation, coordination, agent communication languages, and agent micro level issues. Sensible roles and tasks in the system motivate more research and make this environment a suitable infrastructure for educational purposes. Arian is a set of implemented agents for RoboCupRescue system. Using Arian agents will speed up implementing agents for this environment. In this paper, we introduce RoboCupRescue simulation environment and Arian agents along with some examples of research issues in this environment. We also present some of RoboCupRescue sub-problems for specific research goals. Although RoboCupRescue can be considered as an application of multi-agent research, in this paper we focus on the suitability of this environment as an infrastructure for multi-agent research and education.