AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Reinforcement, Psychology

Showing 111 to 120 of 255 articles

Clear Filters

Design of Travel Route Identification and Scheduling System Based on Artificial Intelligence-Aided Image Segmentation.

Computational intelligence and neuroscience
This study designs a travel recognition and scheduling system using artificial intelligence and image segmentation techniques. To address the problem of low division quality of current point division algorithms, this study proposes a streaming graph ...

Periodic event-triggered adaptive tracking control design for nonlinear discrete-time systems via reinforcement learning.

Neural networks : the official journal of the International Neural Network Society
In this paper, an event-triggered control scheme with periodic characteristic is developed for nonlinear discrete-time systems under an actor-critic architecture of reinforcement learning (RL). The periodic event-triggered mechanism (ETM) is construc...

Generalized Single-Vehicle-Based Graph Reinforcement Learning for Decision-Making in Autonomous Driving.

Sensors (Basel, Switzerland)
In the autonomous driving process, the decision-making system is mainly used to provide macro-control instructions based on the information captured by the sensing system. Learning-based algorithms have apparent advantages in information processing a...

Active learning of causal structures with deep reinforcement learning.

Neural networks : the official journal of the International Neural Network Society
We study the problem of experiment design to learn causal structures from interventional data. We consider an active learning setting in which the experimenter decides to intervene on one of the variables in the system in each step and uses the resul...

Cellular Network Power Allocation Algorithm Based on Deep Reinforcement Learning and Artificial Intelligence.

Computational intelligence and neuroscience
In the shortest path planning problem, the old algorithm usually has many defects, such as the robot's cognition being contrary to reality, the lack of practical operation feasibility, or the limitation of problem processing. Nowadays, with deep lear...

Exploring Potential Energy Surfaces Using Reinforcement Machine Learning.

Journal of chemical information and modeling
Reinforcement machine learning is implemented to survey a series of model potential energy surfaces and ultimately identify the global minima point. Through sophisticated reward function design, the introduction of an optimizing target, and incorpora...

A Novel Mean-Field-Game-Type Optimal Control for Very Large-Scale Multiagent Systems.

IEEE transactions on cybernetics
In this article, a decentralized adaptive optimal controller based on the emerging mean-field game (MFG) and self-organizing neural networks (NNs) has been developed for multiagent systems (MASs) with a large population and uncertain dynamics. This d...

Fast Task Adaptation Based on the Combination of Model-Based and Gradient-Based Meta Learning.

IEEE transactions on cybernetics
Deep reinforcement learning (DRL) recently has attained remarkable results in various domains, including games, robotics, and recommender system. Nevertheless, an urgent problem in the practical application of DRL is fast adaptation. To this end, thi...

The Intelligent Path Planning System of Agricultural Robot via Reinforcement Learning.

Sensors (Basel, Switzerland)
Agricultural robots are one of the important means to promote agricultural modernization and improve agricultural efficiency. With the development of artificial intelligence technology and the maturity of Internet of Things (IoT) technology, people p...

Pruning recurrent neural networks replicates adolescent changes in working memory and reinforcement learning.

Proceedings of the National Academy of Sciences of the United States of America
Adolescent development is characterized by an improvement in multiple cognitive processes. While performance on cognitive operations improves during this period, the ability to learn new skills quickly, for example, a new language, decreases. During ...