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Policy

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Path Integral Policy Improvement With Population Adaptation.

IEEE transactions on cybernetics
Path integral policy improvement (PI) is known to be an efficient reinforcement learning algorithm, particularly, if the target system is a high-dimensional dynamical system. However, PI, and its existing extensions, have adjustable parameters, on wh...

Evaluation for hierarchical diagnosis and treatment policy proposals in China: A novel multi-attribute group decision-making method with multi-parametric distance measures.

The International journal of health planning and management
The policy 'hierarchical medical treatment system' promulgated by the State Council of China is an effective way to solve the problem of insufficient and unbalanced medical resources. In response, governments in different provinces explore a variety ...

A hybridization of distributed policy and heuristic augmentation for improving federated learning approach.

Neural networks : the official journal of the International Neural Network Society
Modifying the existing models of classifiers' operation is primarily aimed at increasing the effectiveness as well as minimizing the training time. An additional advantage is the ability to quickly implement a given solution to the real needs of the ...

Advancing health equity with artificial intelligence.

Journal of public health policy
Population and public health are in the midst of an artificial intelligence revolution capable of radically altering existing models of care delivery and practice. Just as AI seeks to mirror human cognition through its data-driven analytics, it can a...

Achieving a 'Good AI Society': Comparing the Aims and Progress of the EU and the US.

Science and engineering ethics
Over the past few years, there has been a proliferation of artificial intelligence (AI) strategies, released by governments around the world, that seek to maximise the benefits of AI and minimise potential harms. This article provides a comparative a...

Learning policy scheduling for text augmentation.

Neural networks : the official journal of the International Neural Network Society
When training deep learning models, data augmentation is an important technique to improve the performance and alleviate overfitting. In natural language processing (NLP), existing augmentation methods often use fixed strategies. However, it might be...

Ensemble Learning Based on Policy Optimization Neural Networks for Capability Assessment.

Sensors (Basel, Switzerland)
Capability assessment plays a crucial role in the demonstration and construction of equipment. To improve the accuracy and stability of capability assessment, we study the neural network learning algorithms in the field of capability assessment and i...

Research on the evolution and driving forces of the manufacturing industry during the "13th five-year plan" period in Jiangsu province of China based on natural language processing.

PloS one
The development of China's manufacturing industry has received global attention. However, research on the distribution pattern, changes, and driving forces of the manufacturing industry has been limited by the accessibility of data. This study propos...

Achieving Equity with Predictive Policing Algorithms: A Social Safety Net Perspective.

Science and engineering ethics
Whereas using artificial intelligence (AI) to predict natural hazards is promising, applying a predictive policing algorithm (PPA) to predict human threats to others continues to be debated. Whereas PPAs were reported to be initially successful in Ge...