32 citations · 51 across the 4 of their papers we have counts for
7 papers
Differential Privacy for Symbolic Systems with Application to Markov Chains
Bo Chen, Kevin Leahy, Austin Jones +1
Data-driven systems are gathering increasing amounts of data from users, and sensitive user data requires privacy protections. In some cases, the data gathered is non-numerical or…
Fast Decomposition of Temporal Logic Specifications for Heterogeneous Teams
Kevin Leahy, Austin Jones, Cristian-Ioan Vasile
In this work, we focus on decomposing large multi-agent path planning problems with global temporal logic goals (common to all agents) into smaller sub-problems that can be solved…
Towards Differential Privacy for Symbolic Systems
Austin Jones, Kevin Leahy, Matthew Hale
In this paper, we develop a privacy implementation for symbolic control systems. Such systems generate sequences of non-numerical data, and these sequences can be represented by wo…
Differentially Private LQ Control
Kasra Yazdani, Austin Jones, Kevin Leahy +1
As multi-agent systems proliferate and share more user data, new approaches are needed to protect sensitive data while still enabling system operation. To address this need, this p…
Privacy in Feedback: The Differentially Private LQG
Matthew Hale, Austin Jones, Kevin Leahy
Information communicated within cyber-physical systems (CPSs) is often used in determining the physical states of such systems, and malicious adversaries may intercept these commun…
Q-Learning for Robust Satisfaction of Signal Temporal Logic Specifications
Derya Aksaray, Austin Jones, Zhaodan Kong +2
This paper addresses the problem of learning optimal policies for satisfying signal temporal logic (STL) specifications by agents with unknown stochastic dynamics. The system is mo…
Robust Satisfaction of Temporal Logic Specifications via Reinforcement Learning
Austin Jones, Derya Aksaray, Zhaodan Kong +2
We consider the problem of steering a system with unknown, stochastic dynamics to satisfy a rich, temporally layered task given as a signal temporal logic formula. We represent the…