A5017397385- Stochastic processes and financial applications
- Economic theories and models
- Mathematical and Theoretical Epidemiology and Ecology Models
- Mathematical Biology Tumor Growth
- Distributed Control Multi-Agent Systems
- Climate Change Policy and Economics
- Advanced Thermodynamics and Statistical Mechanics
- Stability and Control of Uncertain Systems
- Game Theory and Applications
- Adaptive Dynamic Programming Control
- Opinion Dynamics and Social Influence
- Insurance, Mortality, Demography, Risk Management
- Reinforcement Learning in Robotics
- Neural Networks Stability and Synchronization
- Complex Systems and Time Series Analysis
- Fault Detection and Control Systems
- Target Tracking and Data Fusion in Sensor Networks
- Control Systems and Identification
- Power System Optimization and Stability
- Complex Network Analysis Techniques
- Advanced Control Systems Optimization
- Smart Grid Security and Resilience
- Electrospun Nanofibers in Biomedical Applications
- Decision-Making and Behavioral Economics
- Evolutionary Game Theory and Cooperation
Shandong University
2016-2025
Qingdao University
2021-2022
Guangdong Open University
2022
Hong Kong Polytechnic University
2021
University of Central Florida
2021
University of California, Los Angeles
2019
University of Newcastle Australia
2013-2014
Dalian University of Technology
2014
Chinese Academy of Sciences
2009-2012
Academy of Mathematics and Systems Science
2009-2012
In this paper, distributed games for large-population multiagent systems with random time-varying parameters are investigated, where the agents coupled via their individual costs and structure a family of independent Markov chains identical generators. The cost function each agent is long-run average tracking-type functional an unknown mean field coupling nonlinear term as "reference signal." To reduce computational complexity, approach applied to construct strategies. population statistics...
This paper investigates social optima of mean field linear-quadratic-Gaussian (LQG) control models with Markov jump parameters. The common objective the agents is to minimize a cost---the cost average whole society. In functions there are coupled terms. First, we consider centralized case and get parameterized equation effect. Then, design set distributed strategies by solving limiting optimal problem in an augmented state space subject consistency requirement for approximation. It shown...
In this technical note, event-based pulse-modulated control is studied for linear stochastic systems with an average quadratic performance over infinite horizon. From the probabilistic representation of solutions to differential equations, analytic expression provided. For stable and critically first-order systems, schemes seeking optimal parameters are given. unstable case, stabilization problem discussed. Unstable (first-order or higher-order) white noises cannot be stabilized probability...
In this technical note, hierarchical games are investigated for multi-agent systems involving a leader and large number of followers with infinite horizon tracking-type costs. By jointly analyzing dynamic equations index functions all agents, set centralized Stackelberg equilibrium strategies is given. Then, by using the mean field approach brute force method, distributed designed. Under mild conditions, it shown that closed-loop system uniformly stable an ε-Stackelberg equilibrium.
This article studies uniform stabilization and social optimality for linear quadratic (LQ) mean field control problems with multiplicative noise, where agents are coupled via dynamics individual costs. The state weights in cost functionals not limited to be positive semidefinite. leads an <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">indefinite</i> LQ problem, which may still well-posed due deep nature of noise. We first obtain a set...
This paper examines mean field linear-quadratic-Gaussian social optimum control with volatility-uncertain common noise. The diffusion terms in the dynamics of agents contain an unknown volatility process driven by a We apply robust optimization approach which all view uncertainty as adversarial player. Based on principle person-by-person optimality and two-step duality technique for stochastic variational analysis, we construct auxiliary optimal problem representative agent. Through solving...
This paper studies the exponential synchronization problem for a new array of nonlinearly and stochastically coupled networks via events-triggered sampling (ETS) by self-adaptive learning. The include following features: 1) Bernoulli stochastic variable is introduced to describe random structural coupling; 2) with positive mean used model coupling strength; 3) continuous time homogeneous Markov chain employed characterize dynamical switching structure pinned node sets. proposed network...
Distributed dynamic average consensus is investigated under quantized communication data. We use a uniform quantizer with constant quantization step-size to deal the saturation caused by error and propose feedback-based distributed protocol suitable for directed time-varying topologies make internal state of each agent's encoder consistent output its neighbors' decoder. For case where topology directed, balanced periodically connected, it shown that if difference reference inputs satisfies...
Summary This paper studies mean‐field games for multiagent systems with control‐dependent multiplicative noises. For the general nonuniform agents, we obtain a set of decentralized strategies by solving an auxiliary limiting optimal control problem subject to consistent approximations. The is further shown be ε ‐Nash equilibrium. integrator systems, design exploiting convexity property problem. It that under mild conditions, all agents achieve mean‐square consensus.
This article studies social optimal control of mean field linear-quadratic-Gaussian models with uncertainty. Specially, the uncertainty is represented by an uncertain drift, which common for all agents. A robust optimization approach applied assuming agents treat drift as adversarial player. In our model, both dynamics and costs are coupled terms, finite- infinite-time horizon cases considered. By examining functional variation exploiting person-by-person optimality principle, we construct...
This paper studies mean field linear-quadratic-Gaussian (LQG) social optimum control for models with a common uncertain drift, where both dynamics and costs of agents involve coupled terms. We adopt robust optimization approach all the view drift as an adversarial player. Based on variational derivation person-by-person optimality principle, we construct auxiliary optimal problem representative agent. By solving combined consistent approximations, set decentralized strategies is designed...