Concurrent systems may execute one of an exponential number of paths resulting in a large number of potential states. This often makes it infeasible to consider all possible behaviors of a system. Scalable formal methods, while not guaranteeing correctness, can provide greater confidence about properties of a system. The talk will describe three such methods: Statistical Model Checking (SMC), Euclidean Model Checking (EMC), and Predictive Runtime Verification (PRV).
Upcoming TCSDLS Events
I will present the 'virtual democracy' framework for the design of ethical AI. In a nutshell, the framework consists of three steps: first, collect preferences from voters on example dilemmas; second, learn models of their preferences, which generalize to any (previously unseen) dilemma; and third, at runtime, predict the voters' preferences on the current dilemma, and aggregate these virtual 'votes' using a voting rule to reach a decision.