Zobrazeno 1 - 10
of 1 357
pro vyhledávání: '"LI Shaoyuan"'
Publikováno v:
智能科学与技术学报, Vol 6, Pp 232-243 (2024)
Parkinson's disease (PD) patients were often accompanied by cognitive impairment, which seriously affected the quality of life, so the over-prediction of cognitive impairment in Parkinson's disease was crucial for clinical diagnosis and intervention.
Externí odkaz:
https://doaj.org/article/dc4f3aad963749ca82fc37b7f6503ab3
We investigate the problem of safe control synthesis for systems operating in environments with uncontrollable agents whose dynamics are unknown but coupled with those of the controlled system. This scenario naturally arises in various applications,
Externí odkaz:
http://arxiv.org/abs/2410.15660
In this paper, we investigate the property verification problem for partially-observed DES from a new perspective. Specifically, we consider the problem setting where the system is observed by two agents independently, each with its own observation.
Externí odkaz:
http://arxiv.org/abs/2409.06588
Autor:
Chen, Qianqian, Li, Shaoyuan
This paper investigates an aperiodic distributed model predictive control approach for multi-agent systems (MASs) in which parameterized synchronization constraints is considered and an innovative self-triggered criterion is constructed. Different fr
Externí odkaz:
http://arxiv.org/abs/2405.11006
Autor:
Chen, Qianqian, Li, Shaoyuan
This paper investigates the distributed model predictive control for an asynchronous nonlinear multi-agent system with external interference via a self-triggered generator and a prediction horizon regulator. First, a shrinking constraint related to t
Externí odkaz:
http://arxiv.org/abs/2405.11005
We investigate the problem of optimal control synthesis for Markov Decision Processes (MDPs), addressing both qualitative and quantitative objectives. Specifically, we require the system to fulfill a qualitative surveillance task in the sense that a
Externí odkaz:
http://arxiv.org/abs/2403.18632
In this paper, we investigate the problem of linear temporal logic (LTL) path planning for multi-agent systems, introducing the new concept of \emph{ordering constraints}. Specifically, we consider a generic objective function that is defined for the
Externí odkaz:
http://arxiv.org/abs/2403.17704
In this paper, we investigate the problem of optimal supervisory control for the discrete event systems under energy constraints. We consider that the execution of events consumes energy and the energy can be replenished at specific reload states. Wh
Externí odkaz:
http://arxiv.org/abs/2402.05564
Synthesis of Temporally-Robust Policies for Signal Temporal Logic Tasks using Reinforcement Learning
This paper investigates the problem of designing control policies that satisfy high-level specifications described by signal temporal logic (STL) in unknown, stochastic environments. While many existing works concentrate on optimizing the spatial rob
Externí odkaz:
http://arxiv.org/abs/2312.05764