5 citations · 28 across the 34 of their papers we have counts for
8 papers · 1 filter
Safeguarded Progress in Reinforcement Learning: Safe Bayesian Exploration for Control Policy Synthesis
Rohan Mitta, Hosein Hasanbeig, Jun Wang +3
This paper addresses the problem of maintaining safety during training in Reinforcement Learning (RL), such that the safety constraint violations are bounded at any point during le…
Verified Compositional Neuro-Symbolic Control for Stochastic Systems with Temporal Logic Tasks
Jun Wang, Haojun Chen, Zihe Sun +1
Several methods have been proposed recently to learn neural network (NN) controllers for autonomous agents, with unknown and stochastic dynamics, tasked with complex missions captu…
Mission-driven Exploration for Accelerated Deep Reinforcement Learning with Temporal Logic Task Specifications
Jun Wang, Hosein Hasanbeig, Kaiyuan Tan +2
This paper addresses the problem of designing control policies for agents with unknown stochastic dynamics and control objectives specified using Linear Temporal Logic (LTL). Recen…
Conformal Temporal Logic Planning using Large Language Models
Jun Wang, Jiaming Tong, Kaiyuan Tan +2
This paper addresses planning problems for mobile robots. We consider missions that require accomplishing multiple high-level sub-tasks, expressed in natural language (NL), in a te…
Uncertainty-bounded Active Monitoring of Unknown Dynamic Targets in Road-networks with Minimum Fleet
Shuaikang Wang, Yiannis Kantaros, Meng Guo
Fleets of unmanned robots can be beneficial for the long-term monitoring of large areas, e.g., to monitor wild flocks, detect intruders, search and rescue. Monitoring numerous dyna…
Neural Lyapunov Control for Discrete-Time Systems
Junlin Wu, Andrew Clark, Yiannis Kantaros +1
While ensuring stability for linear systems is well understood, it remains a major challenge for nonlinear systems. A general approach in such cases is to compute a combination of…