Title: Interdiction Games on Markovian PERT Networks
Speaker: Eli Gutin
Affiliation: School of Industrial and Systems Engineering – Georgia Institute of Technology
Location: Room 218 Huxley Building
Time: 3:00pm

Abstract. In a stochastic interdiction game a proliferator aims to minimize the expected duration of a nuclear weapons development project, while an interdictor endeavors to maximize the project duration by delaying some of the project tasks. We formulate static and dynamic versions of the interdictor’s decision problem where the interdiction plan is either pre-committed or adapts to new information revealed over time, respectively. The static model gives rise to a stochastic program, while the dynamic model is formalized as a multiple optimal stopping problem in continuous time and with decision-d ependent information. Under a Markov assumption, we prove that the static model reduces to a mixed-integer linear program, while the dynamic model reduces to a finite Markov decision process in discrete time that can be solved via efficient value iteration. We then generalize the dynamic model to account for uncertainty in the outcomes of the interdiction actions. We also discuss a crashing game where the proliferator can use limited resources to expedite tasks so as to counterbalance the interdictor’s efforts. The resulting problem can be formulated as a robust Markov decision process.

About the speaker. Eli Gutin completed his MEng in Computing at Imperial College in 2012. His prize-winning final year project on “Interdiction Games on Markovian PERT networks” was supervised by Daniel Kuhn & Wolfram Wiesemann. A year later, it was submitted for publication and is the subject of today’s talk.