76 citations · 308 across the 72 of their papers we have counts for
6 papers · 1 filter
Asynchronous Zeroth-Order Distributed Optimization with Residual Feedback
Yi Shen, Yan Zhang, Scott Nivison +2
We consider a zeroth-order distributed optimization problem, where the global objective function is a black-box function and, as such, its gradient information is inaccessible to t…
Learning without Knowing: Unobserved Context in Continuous Transfer Reinforcement Learning
Chenyu Liu, Yan Zhang, Yi Shen +1
In this paper, we consider a transfer Reinforcement Learning (RL) problem in continuous state and action spaces, under unobserved contextual information. For example, the context c…
Failing with Grace: Learning Neural Network Controllers that are Boundedly Unsafe
Panagiotis Vlantis, Leila J. Bridgeman, Michael M. Zavlanos
In this work, we consider the problem of learning a feed-forward neural network controller to safely steer an arbitrarily shaped planar robot in a compact and obstacle-occluded wor…
Formal Verification of Stochastic Systems with ReLU Neural Network Controllers
Shiqi Sun, Yan Zhang, Xusheng Luo +3
In this work, we address the problem of formal safety verification for stochastic cyber-physical systems (CPS) equipped with ReLU neural network (NN) controllers. Our goal is to fi…
Learning Optimal Strategies for Temporal Tasks in Stochastic Games
Alper Kamil Bozkurt, Yu Wang, Michael M. Zavlanos +1
Synthesis from linear temporal logic (LTL) specifications provides assured controllers for systems operating in stochastic and potentially adversarial environments. Automatic synth…
Temporal Logic Task Allocation in Heterogeneous Multi-Robot Systems
Xusheng Luo, Michael M. Zavlanos
In this paper, we consider the problem of optimally allocating tasks, expressed as global Linear Temporal Logic (LTL) specifications, to teams of heterogeneous mobile robots. The r…