77 citations · 187 across the 16 of their papers we have counts for
7 papers · 1 filter
Time-Incremental Learning from Data Using Temporal Logics
Erfan Aasi, Mingyu Cai, Cristian Ioan Vasile +1
Real-time and human-interpretable decision-making in cyber-physical systems is a significant but challenging task, which usually requires predictions of possible future events from…
Intelligent Traffic Light via Policy-based Deep Reinforcement Learning
Yue Zhu, Mingyu Cai, Chris Schwarz +2
Intelligent traffic lights in smart cities can optimally reduce traffic congestion. In this study, we employ reinforcement learning to train the control agent of a traffic light on…
An Ultra-Reliable Low-Latency Non-Binary Polar Coded SCMA Scheme
Shufeng Li, Mingyu Cai, Libiao Jin +3
The joint transmission scheme of polar codes and sparse code multiple access (SCMA) has been regarded as a promising technology for future wireless communication systems. However,…
Online Motion Planning with Soft Metric Interval Temporal Logic in Unknown Dynamic Environment
Zhiliang Li, Mingyu Cai, Shaoping Xiao +1
Motion planning of an autonomous system with high-level specifications has wide applications. However, research of formal languages involving timed temporal logic is still under in…
Safety-Critical Learning of Robot Control with Temporal Logic Specifications
Mingyu Cai, Cristian-Ioan Vasile
Reinforcement learning (RL) is a promising approach. However, success is limited to real-world applications, because ensuring safe exploration and facilitating adequate exploitatio…
Modular Deep Reinforcement Learning for Continuous Motion Planning with Temporal Logic
Mingyu Cai, Mohammadhosein Hasanbeig, Shaoping Xiao +2
This paper investigates the motion planning of autonomous dynamical systems modeled by Markov decision processes (MDP) with unknown transition probabilities over continuous state a…
Reinforcement Learning Based Temporal Logic Control with Soft Constraints Using Limit-deterministic Generalized Buchi Automata
Mingyu Cai, Shaoping Xiao, Zhijun Li +1
This paper studies the control synthesis of motion planning subject to uncertainties. The uncertainties are considered in robot motions and environment properties, giving rise to t…