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Policy

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Intelligent design of the chiral metasurfaces for flexible targets: combining a deep neural network with a policy proximal optimization algorithm.

Optics express
Recently, deep reinforcement learning (DRL) for metasurface design has received increased attention for its excellent decision-making ability in complex problems. However, time-consuming numerical simulation has hindered the adoption of DRL-based des...

Finding patterns in policy questions.

Scientific reports
To help advance exchanges between science and policy, a useful first step is to examine the questions which policymakers pose to scientists. The style of a question indicates what the asker is motivated to know, and how they might use that knowledge....

Event-triggered adaptive dynamic programming for decentralized tracking control of input constrained unknown nonlinear interconnected systems.

Neural networks : the official journal of the International Neural Network Society
This paper addresses decentralized tracking control (DTC) problems for input constrained unknown nonlinear interconnected systems via event-triggered adaptive dynamic programming. To reconstruct the system dynamics, a neural-network-based local obser...

Representation learning for continuous action spaces is beneficial for efficient policy learning.

Neural networks : the official journal of the International Neural Network Society
Deep reinforcement learning (DRL) breaks through the bottlenecks of traditional reinforcement learning (RL) with the help of the perception capability of deep learning and has been widely applied in real-world problems. While model-free RL, as a clas...

Deep Deterministic Policy Gradient-Based Autonomous Driving for Mobile Robots in Sparse Reward Environments.

Sensors (Basel, Switzerland)
In this paper, we propose a deep deterministic policy gradient (DDPG)-based path-planning method for mobile robots by applying the hindsight experience replay (HER) technique to overcome the performance degradation resulting from sparse reward proble...

The Impact of SO Emissions Trading Scheme on Firm's Environmental Performance: A Channel from Robot Application.

International journal of environmental research and public health
Improving the environmental performance of enterprises is the key to achieving the goal of energy conservation, emission reduction and green development. This paper investigates the causal impact on the firm's environmental performance of China's SO ...

Evaluation of roadside air quality using deep learning models after the application of the diesel vehicle policy (Euro 6).

Scientific reports
Euro 6 is the latest vehicle emission standards for pollutants such as CO, NO and PM, that all new vehicles must comply, and it was introduced in September 2015 in South Korea. This study examined the effect of Euro 6 by comparing the measured pollut...

Vision-Based Efficient Robotic Manipulation with a Dual-Streaming Compact Convolutional Transformer.

Sensors (Basel, Switzerland)
Learning from visual observation for efficient robotic manipulation is a hitherto significant challenge in Reinforcement Learning (RL). Although the collocation of RL policies and convolution neural network (CNN) visual encoder achieves high efficien...

Excellence in Total Worker Health® and an Interview With Dr Laura Linnan.

American journal of health promotion : AJHP
The National Institute of Occupational Safety and Health (NIOSH) defines as "policies, programs and practices that integrate protection from work-related safety and health hazards with promotion of injury and illness prevention efforts to advance wo...

Priority-based replenishment policy for robotic dispensing in central fill pharmacy systems: a simulation-based study.

Health care management science
In recent years, companies that operate pharmacy store chains have adopted centralized and automated fulfillment systems, which are called Central Fill Pharmacy Systems (CFPS). The Robotic Dispensing System (RDS) plays a crucial role by automatically...