Agent-Based Disaster Simulation Evaluation and its Probability Model Interpretation

Agent-based simulations enable the simulation of social phenomenon by representing human behaviors using agents. Human actions such as evacuating to safe havens or extinguishing fires in disaster areas are important during earthquakes. The inclusion of human actions in calculating the damage at disaster sites provides useful data to local governments for planning purposes. In order to practically apply these simulation results, these results should be tested using actual data. Further, these results should be analyzed and explained in a manner that people who are not agent programmers can also understand easily. First, the possibility of applying agent-based approaches to social tasks is shown by comparing the simulation results with those obtained from other methods. Next, we propose a method to present agent behaviors using a probability model and discuss the results of applying this method to the RoboCup Rescue simulation data. These will delve into future research topics for developing agent based social simulations to practical ones.