Innovations in Game Theoretic Modeling for Terrorism and Natural Disasters

Principal Investigator: Jun Zhuang


The primary focus of the research at the University at Buffalo has been to explore new decision and risk analysis models to better prepare for and respond to man-made and natural disasters. We use game theory to model the strategic interactions among players in homeland security, including terrorists, the federal/local/foreign governments, private companies, non-governmental organizations (NGOs), and private citizens. Figure 1 shows the general research framework. The governments and private citizens seek to protect lives, property, and critical infrastructure from both adaptive terrorists and non-adaptive natural disasters. In particular, the federal government can provide grants to local governments and foreign aid to foreign governments, and all levels of government can provide pre-disaster preparation/mitigation (including hazard/vulnerability analysis, hazard mitigation, emergency preparedness, and recovery preparedness) and post-disaster relief (including emergency response and disaster recovery) to private citizens. Private citizens can also, of course, make their own investments. The private corporations receive regulations from the government, pay taxes to the government, and balance efforts between safety and production. The NGOs receive donations and also play a key role in disaster preparedness and relief.   This has been again a productive year for this CREATE-sponsored project (see Section 4 for details). We have 11 peer-reviewed journal papers published/accepted with 8 additional papers under review with journals. The research group (the PI and his students) made 45 conference presentations and the PI spoke at over 12 invited research seminars and guest lectures. The PI graduated one Ph.D. student and a couple of MS students with thesis. One of the PI’s Ph.D. students was the Finalist of the 2012 Decision Analysis Society Student Paper Award. Another one of the PI’s Ph.D. students recently received the 2011 Student Paper Award from the Society for Risk Analysis’s Decision Analysis and Risk Specialty Group.