| 1 |
Risk Probability Minimization Problems for Continuous-Time Markov Decision Processes on Finite Horizon
Huo HF, Guo XP
IEEE Transactions on Automatic Control, 65(7), 3199, 2020 |
| 2 |
A model-based deep reinforcement learning method applied to finite-horizon optimal control of nonlinear control-affine system
Kim JW, Park BJ, Yoo H, Oh TH, Lee JH, Lee JM
Journal of Process Control, 87, 166, 2020 |
| 3 |
Markov decision processes with sequential sensor measurements
El Chamie M, Janak D, Acikmese B
Automatica, 103, 450, 2019 |
| 4 |
Finite-horizon multi-objective generalized H-2 control with transients
Balandin DV, Biryukov RS, Kogan MM
Automatica, 106, 27, 2019 |
| 5 |
Chance-constrained H-infinity control for a class of time-varying systems with stochastic nonlinearities: The finite-horizon case
Tian EG, Wang ZD, Zou L, Yue D
Automatica, 107, 296, 2019 |
| 6 |
Unified Approach to Convex Robust Distributed Control Given Arbitrary Information Structures
Furieri L, Kamgarpour M
IEEE Transactions on Automatic Control, 64(12), 5199, 2019 |
| 7 |
Envelope-constrained H-infinity filtering for nonlinear systems with quantization effects: The finite horizon case
Ma LF, Wang ZD, Han QL, Lam HK
Automatica, 93, 527, 2018 |
| 8 |
Finite-horizon LQR controller for partially-observed Boolean dynamical systems
Imani M, Braga-Neto UM
Automatica, 95, 172, 2018 |
| 9 |
RISK SENSITIVE PORTFOLIO OPTIMIZATION IN A JUMP DIFFUSION MODEL WITH REGIMES
Das MK, Goswami A, Rana N
SIAM Journal on Control and Optimization, 56(2), 1550, 2018 |
| 10 |
Constrained Continuous-Time Markov Decision Processes on the Finite Horizon
Guo XP, Huang YH, Zhang Y
Applied Mathematics and Optimization, 75(2), 317, 2017 |
