most citedStatistically Model Checking PCTL Specifications on Markov Decision Processes via Reinforcement Learning

1 citations · 1 across the 2 of their papers we have counts for

collaborators

5 papers

math.OC2020

Verifying Stochastic Hybrid Systems with Temporal Logic Specifications via Model Reduction

Yu Wang, Nima Roohi, Matthew West +2

We present a scalable methodology to verify stochastic hybrid systems. Using the Mori-Zwanzig reduction method, we construct a finite state Markov chain reduction of a given stocha…

cs.LO2020

Context-Aware Temporal Logic for Probabilistic Systems

Mahmoud Elfar, Yu Wang, Miroslav Pajic

In this paper, we introduce the context-aware probabilistic temporal logic (CAPTL) that provides an intuitive way to formalize system requirements by a set of PCTL objectives with…

cs.LG20201 cited

Statistically Model Checking PCTL Specifications on Markov Decision Processes via Reinforcement Learning

Yu Wang, Nima Roohi, Matthew West +2

Probabilistic Computation Tree Logic (PCTL) is frequently used to formally specify control objectives such as probabilistic reachability and safety. In this work, we focus on model…

cs.RO2019

Hyperproperties for Robotics: Planning via HyperLTL

Yu Wang, Siddhartha Nalluri, Miroslav Pajic

There is a growing interest on formal methods-based robotic planning for temporal logic objectives. In this work, we extend the scope of existing synthesis methods to hyper-tempora…

cs.LO2019

Statistical Verification of Hyperproperties for Cyber-Physical System

Yu Wang, Mojtaba Zarei, Borzoo Bonakdarpour +1

Many important properties of cyber-physical systems (CPS) are defined upon the relationship between multiple executions simultaneously in continuous time. Examples include probabil…