연속시간 확률제어 문제에서 측정가능 선택 기법과 동적계획법의 응용
연속시간 확률제어/정지 문제에 대한 동적계획법 원리를 측정가능 선택 기법을 사용하여 도출하고, 이를 통해 최적 제어/정지 과정의 특성화와 가치함수의 점근해 표현 등을 얻을 수 있다.
Distributionally Robust Stochastic Data-Driven Predictive Control with Optimized Feedback Gain
This paper proposes a data-driven stochastic predictive control strategy that utilizes distributionally robust conditional value-at-risk constraints and optimizes the feedback gain within the control policy, providing improved safety and flexibility compared to previous approaches.
Computational Method for Singular Control of Reflected Brownian Motion with Applications to Queueing Networks
This paper presents a computational method for solving singular stochastic control problems motivated by queueing theory applications. The method approximates the original singular control problem by a drift control problem, which can be solved efficiently using a recently developed simulation-based approach.
Risk-Aware Fixed-Time Stabilization of Stochastic Systems with Measurement Uncertainty
The paper introduces novel classes of risk-aware fixed-time control Lyapunov functions (RA-FxT-CLFs) and risk-aware path-integral control Lyapunov functions (RA-PI-CLFs) to certify that a stochastic, nonlinear system's trajectories reach a goal set within a fixed-time with a specified probability, despite the presence of measurement uncertainty.
Q-Learning for Stochastic Control under General Information Structures and Non-Markovian Environments
Presenting a convergence theorem for stochastic iterations, particularly Q-learning, under general, possibly non-Markovian, stochastic environments.
Soft-constrained Schrödinger Bridge: A Stochastic Control Approach
提案された新しい制御問題「ソフト拘束シュレディンガーブリッジ（SSB）」の理論的導出と解決策に焦点を当てる。
Q-Learning for Stochastic Control under General Information Structures and Non-Markovian Environments: Convergence Theorems and Applications
The authors present convergence theorems for Q-learning under non-Markovian environments, discussing implications and applications to various stochastic control problems.
