In this section, we explain the simulation content, agent type and behavior, themes of agent development and development environment issues.
Overview of RRS
The RRS is a research platform that simulates disaster-affected areas and disaster-relief activities on a computer (Takahashi, 2001). It can handle disaster-relief activities over approximately 5 hours from the occurrence of a disaster.
Figure 1 shows the activities of agents in the RRS. In the disaster-relief activities, we control six types of agents, namely AmbulanceTeam, FireBrigade, PoliceForce, and the headquarters of each of these units (AmbulanceCentre, FireStation, and PoliceOffice). In addition, there are Civilian agents to simulate civilians in disaster situations.
These agents rescue other agents that cannot move by themselves. They rescue targets from debris and transport them to evacuation centers.
These agents extinguish fires in buildings. They extinguish the fire by discharging the water stored in their tank. It is necessary to supply water when the tank becomes empty.
These agents clear road blockages. They enable other agents to access certain areas by removing obstacles.
These agents are headquarters. These agents are only for enabling communication. They cannot move but they are also not injured.
In the competition, these agents move automatically to evacuation centers.
The RRS simulator consists of a kernel that manages the progress of the simulation. In addition, there are sub-simulator components that simulate disaster situations and agent programs. The simulation proceeds at the rate of one step per minute. The time allowed for calculating one step of an agent is limited to 1 s. Before the start of the simulation, as a pre-calculation stage, it is possible to calculate initial data using only topographical information (Faraji, 2016).
The RRS can be used to research applications of artificial intelligence and information science to natural-disaster rescue problems. In the RRS, five research tasks of are advocated in particular, namely Group Formation, Path Planning, Search, Multi-task Allocation, and Communication (Skinner, 2010). Every year, competitions using agent programs are held for the purpose of technical exchange.
Figure 1. Agents and objects in the RoboCup Rescue Simulation