activity
20162022
most citedNeural Certificates for Safe Control Policies

43 citations · 60 across the 5 of their papers we have counts for

collaborators

9 papers

eess.SY2022

Cooperative Tuning of Multi-Agent Optimal Control Systems

Zehui Lu, Wanxin Jin, Shaoshuai Mou +1

This paper investigates the problem of cooperative tuning of multi-agent optimal control systems, where a network of agents (i.e. multiple coupled optimal control systems) adjusts…

cs.LG2021

Safe Pontryagin Differentiable Programming

Wanxin Jin, Shaoshuai Mou, George J. Pappas

We propose a Safe Pontryagin Differentiable Programming (Safe PDP) methodology, which establishes a theoretical and algorithmic framework to solve a broad class of safety-critical…

eess.SY20212 cited

Towards Resilience for Multi-Agent -Learning

Yijing Xie, Shaoshuai Mou, Shreyas Sundaram

This paper considers the multi-agent reinforcement learning (MARL) problem for a networked (peer-to-peer) system in the presence of Byzantine agents. We build on an existing distri…

eess.SY202043 cited

Neural Certificates for Safe Control Policies

Wanxin Jin, Zhaoran Wang, Zhuoran Yang +1

This paper develops an approach to learn a policy of a dynamical system that is guaranteed to be both provably safe and goal-reaching. Here, the safety means that a policy must not…

eess.SY2020

Distributed traffic control for a large-scale urban network

Viet Hoang Pham, Kazunori Sakurama, Shaoshuai Mou +1

Motivated by the fact that intelligent traffic control systems have become inevitable demand to cope with the risk of traffic congestion in urban areas, this paper develops a distr…

cs.CY201915 cited

Resilient Cyberphysical Systems and their Application Drivers: A Technology Roadmap

Somali Chaterji, Parinaz Naghizadeh, Muhammad Ashraful Alam +14

Cyberphysical systems (CPS) are ubiquitous in our personal and professional lives, and they promise to dramatically improve micro-communities (e.g., urban farms, hospitals), macro-…