Abstract
Computational game theory has become a powerful
tool to address critical issues in security and sustainability. Casting the security resource allocation
problem as a Stackelberg game, novel algorithms
have been developed to provide randomized security resource allocations. These algorithms have
led to deployed security-game based decision aids
for many real-world security domains including
infrastructure security and wildlife protection. We
contribute to this community by addressing several major research challenges in complex security
resource allocation, including dynamic payoffs,
uncertainty, protection externality, games on networks, and strategic secrecy. We also analyze
optimal security resource allocation in many potential application domains including cyber security.
Furthermore, we apply game theory to reasoning
optimal policy in deciding taxi pricing scheme and
EV charging placement and pricing