Results 131 to 140 of about 85,002 (312)

United States Current Account Deficits: A Stochastic Optimal Control Analysis [PDF]

open access: yes
The "Pessimists" and the "Optimists" disagree whether the US external deficits and the associated buildup of US net foreign liabilities are problems that require urgent attention. A warning signal should be that the debt ratio deviates significantly from
Jerome L. Stein
core  

ChicGrasp: Imitation‐Learning‐Based Customized Dual‐Jaw Gripper Control for Manipulation of Delicate, Irregular Bio‐Products

open access: yesAdvanced Robotics Research, EarlyView.
Automated poultry processing lines still rely on humans to lift slippery, easily bruised carcasses onto a shackle conveyor. Deformability, anatomical variance, and hygiene rules make conventional suction and scripted motions unreliable. We present ChicGrasp, an end‐to‐end hardware‐software co‐designed imitation learning framework, to offer a ...
Amirreza Davar   +8 more
wiley   +1 more source

Stochastic Optimal Control, International Finance and Debt [PDF]

open access: yes
We use stochastic optimal control-dynamic programming (DP) to derive the optimal foreign debt/net worth, consumption/net worth, current account/net worth, and endogenous growth rate in an open economy.
Jerome L. Stein, Wendell Fleming
core  

Jump LQ-optimal control for discrete-time Markovian systems with stochastic inputs

open access: yes, 2015
In this paper we consider the discrete-time LQ-optimal control problem for the class of linear systems with Markovian jump parameters and additive Ct-stochastic input. The state-space of the Markov chain is assumed to be a countably infinite set.
Costa, OLV, do Val, JBR
core   +1 more source

LLM‐Integrated Human–Robot Interaction System for Microrobots

open access: yesAdvanced Robotics Research, EarlyView.
This paper proposes an LLM‐based control framework for guiding microrobots using human natural language. This framework can convert the natural human speech into safe and executable command sets for reliable navigation in complex environments. The experimental results show high accuracy and robustness in task performance, demonstrating the potential of
Bairong Zhu, Amar Salehi, Tingting Yu
wiley   +1 more source

DRIVE‐SAFE: Data‐Driven Robustness and Informed Validation for Evolving Specifications via Formal Evaluation

open access: yesAdvanced Robotics Research, EarlyView.
DRIVE‐SAFE evaluates learning‐based, black‐box autonomous driving policies against evolving temporal safety requirements using Signal Temporal Logic robustness metrics. It aggregates distributional robustness measures with domain‐informed weights to guide iterative retraining.
Kristy Sakano   +3 more
wiley   +1 more source

Theory of Stochastic Optimal Economic Growth

open access: yes
This paper is a survey of the theory of stochastic optimal economic growth.International Development,
Olson, Lars J., Roy, Santanu
core  

Distributionally robust uertainty quantification via data-driven stochastic optimal control

open access: yes, 2023
This letter studies optimal control problems of unknown linear systems subject to stochastic disturbances of uncertain distribution. Uncertainty about the stochastic disturbances is usually described via ambiguity sets of probability measures or ...
Pan, Guanru, Faulwasser, Timm
core  

N, S Co‐Doped Carbon Quantum Dots‐Riboflavin Composite Photosensitizers for Enhanced Iontophoresis‐Assisted Corneal Cross‐Linking

open access: yesAdvanced Science, EarlyView.
This study explores the use of N, S co‐doped carbon quantum dots (NS‐CQDs) as carriers for riboflavin, creating NS‐CQDs‐RF composite photosensitizers. These composites improve riboflavin absorption, enhance ROS generation efficiency, and preserve corneal epithelium integrity.
Tinghong Xu   +9 more
wiley   +1 more source

Robust Optimal Control for a Consumption-investment Problem [PDF]

open access: yes
We give an explicit PDE characterization for the solution of the problem of maximizing the utility of both terminal wealth and intertemporal consumption under model uncertainty.
Alexander Schied
core  

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