AIMC Topic: Policy

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Predicting technological innovation in new energy vehicles based on an improved radial basis function neural network for policy synergy.

PloS one Aug 25, 2022
Policy synergy is necessary to promote technological innovation and sustainable industrial development. A radial basis function (RBF) neural network model with an automatic coding machine and fractional momentum was proposed for the prediction of tec...
Inventions Policy Neural Networks, Computer Physical Phenomena China Industry
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Policy Design for an Ankle-Foot Orthosis Using Simulated Physical Human-Robot Interaction via Deep Reinforcement Learning.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society Aug 11, 2022
This paper presents a novel approach for designing a robotic orthosis controller considering physical human-robot interaction (pHRI). Computer simulation for this human-robot system can be advantageous in terms of time and cost due to the laborious n...
Computer Simulation Foot Orthoses Walking Biomechanical Phenomena Ankle Gait Humans Robotics Policy
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CLSQL: Improved Q-Learning Algorithm Based on Continuous Local Search Policy for Mobile Robot Path Planning.

Sensors (Basel, Switzerland) Aug 8, 2022
How to generate the path planning of mobile robots quickly is a problem in the field of robotics. The Q-learning(QL) algorithm has recently become increasingly used in the field of mobile robot path planning. However, its selection policy is blind in...
Policy Robotics Computer Simulation Algorithms
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Intelligent Smart Marine Autonomous Surface Ship Decision System Based on Improved PPO Algorithm.

Sensors (Basel, Switzerland) Jul 31, 2022
With the development of artificial intelligence technology, the behavior decision-making of an intelligent smart marine autonomous surface ship (SMASS) has become particularly important. This research proposed local path planning and a behavior decis...
Humans Ships Policy Artificial Intelligence Neural Networks, Computer Algorithms
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Predicting age and gender from network telemetry: Implications for privacy and impact on policy.

PloS one Jul 21, 2022
The systematic monitoring of private communications through the use of information technology pervades the digital age. One result of this is the potential availability of vast amount of data tracking the characteristics of mobile network users. Such...
Machine Learning Neural Networks, Computer Privacy Telemetry Humans Policy
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Frame-Correlation Transfers Trigger Economical Attacks on Deep Reinforcement Learning Policies.

IEEE transactions on cybernetics Jul 19, 2022
Adversarial attack can be deemed as a necessary prerequisite evaluation procedure before the deployment of any reinforcement learning (RL) policy. Most existing approaches for generating adversarial attacks are gradient based and are extensive, viz.,...
Markov Chains Reinforcement, Psychology Policy Learning Machine Learning
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Metamodeling for Policy Simulations with Multivariate Outcomes.

Medical decision making : an international journal of the Society for Medical Decision Making Jun 23, 2022
PURPOSE: Metamodels are simplified approximations of more complex models that can be used as surrogates for the original models. Challenges in using metamodels for policy analysis arise when there are multiple correlated outputs of interest. We devel...
Normal Distribution Linear Models Neural Networks, Computer Humans Policy Algorithms
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Legal concerns in health-related artificial intelligence: a scoping review protocol.

Systematic reviews Jun 17, 2022
BACKGROUND: Medical innovations offer tremendous hope. Yet, similar innovations in governance (law, policy, ethics) are likely necessary if society is to realize medical innovations' fruits and avoid their pitfalls. As innovations in artificial intel...
Humans Scoping Reviews As Topic Policy Artificial Intelligence
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A universal adversarial policy for text classifiers.

Neural networks : the official journal of the International Neural Network Society Jun 16, 2022
Discovering the existence of universal adversarial perturbations had large theoretical and practical impacts on the field of adversarial learning. In the text domain, most universal studies focused on adversarial prefixes which are added to all texts...
Policy Semantics Machine Learning Neural Networks, Computer
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Efficient Path Planning for Mobile Robot Based on Deep Deterministic Policy Gradient.

Sensors (Basel, Switzerland) May 8, 2022
When a traditional Deep Deterministic Policy Gradient (DDPG) algorithm is used in mobile robot path planning, due to the limited observable environment of mobile robots, the training efficiency of the path planning model is low, and the convergence s...
Policy Computer Simulation Robotics Neural Networks, Computer Algorithms
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