How should resources be allocated to ensure security against adversaries? This question poses a wide array of challenging problems, given one often has a limited amount of resources to allocate, incomplete knowledge about adversarial behavior, and limited information about environmental conditions. In this talk, I will cover recent results that highlight how informational elements impact performance in competitive resource allocation games. We first establish novel results for General Lotto games under incomplete information, where the relationship between informational availability, resource budgets, and expected performance guarantees is characterized. Leveraging these results, we then focus on the problem of a coordinator that delegates resources to multiple sub-teams that compete against adversarial threats. Here, we show how randomizing the delegations induces asymmetric informational environments between the teams and adversaries, and demonstrate that exploiting such asymmetries can result in a four-fold performance improvement over deterministic delegations. Lastly, and if time permits, we show that publicly announcing strategic intentions to an opponent can have competitive advantages in several different adversarial contexts.
Keith Paarporn received his B.S. in Electrical Engineering from the University of Maryland, College Park in 2013, his M.S. in Electrical and Computer Engineering from the Georgia Institute of Technology in 2016, and his Ph.D. in Electrical and Computer Engineering from the Georgia Institute of Technology in 2018. Since 2018, he is a postdoctoral scholar in the Electrical and Computer Engineering Department at the University of California, Santa Barbara. His research interests include game theory, multi-agent systems, and evolutionary dynamics.