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.
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