Swarm intelligence, social force and multi-agent modeling of heroic altruism behaviors under collective risks

摘要

Terrorists usually choose to attack soft targets, with low self-protection abilities and resistance strengths, such as schools, campus, public squares, railway stations, etc. Under great panic, civilians attacked tend to escape aimlessly and disorderly. Hence, colliding, pushing, and trampling will take place and lead to indirect deaths and injuries. If some heroes with the spirit of altruism, coming from civilians, stand up and fight terrorists bravely, the injuries and deaths will be greatly reduced. Agent-based modeling is built to explore the role of heroes during terrorist attacks. The particle system of three categories of agents, civilians, terrorists & heroes, is built to simulate the Peshawar School Case in 2014. Multiple action rules and mechanisms are introduced, such as swarm intelligence, information communication, self-organized behaviors, and heroic behaviors. We run each simulation repeatedly for 100 times to obtain averaged (robust) outcomes. The optimal combination of parameters, which best matches real outcomes, will be solved accordingly. It indicates that: (a) the self-organizing of crowd behaviors greatly improves the survival rate of civilians. Hence, well-planned trainings of counter-terrorists emergence responses can enhance capabilities of civilians; (b) people should learn from birds’ swarm behavior in crowd evacuations. As a swarm intelligence pathway, small groups and information sharing during crowd escape simulations can greatly improve survival rates; and (c) the society should encourage more people to be altruistic heroes who are acting prosocially. Besides, it suggests that more heroes bring safer overall outcomes for civilians and even for heroes themselves.