Machine learning control information

Machine learning control (MLC) is a subfield of machine learning, intelligent control and control theory which solves optimal control problems with methods...

Machine learning (ML) is a field of study in artificial intelligence concerned with the development and study of statistical algorithms that can learn...

outline is provided as an overview of and topical guide to machine learning: Machine learning – a subfield of soft computing within computer science that...

Quantum machine learning is the integration of quantum algorithms within machine learning programs. The most common use of the term refers to machine learning...

page is a timeline of machine learning. Major discoveries, achievements, milestones and other major events in machine learning are included. History of...

Applying classical methods of machine learning to the study of quantum systems is the focus of an emergent area of physics research. A basic example of...

Reinforcement learning (RL) is an interdisciplinary area of machine learning and optimal control concerned with how an intelligent agent ought to take...

predictive analysis and insight discovery. Artificial intelligence and machine learning have become key enablers to leverage data in production in recent years...

Machine learning in bioinformatics is the application of machine learning algorithms to bioinformatics, including genomics, proteomics, microarrays, systems...

control Machine learning control Reinforcement learning Bayesian control Fuzzy control Neuro-fuzzy control Expert Systems Genetic control New control...

intelligence and machine learning techniques are used in video games for a wide variety of applications such as non-player character (NPC) control and procedural...

In statistics and machine learning, ensemble methods use multiple learning algorithms to obtain better predictive performance than could be obtained from...

Supervised learning (SL) is a paradigm in machine learning where input objects (for example, a vector of predictor variables) and a desired output value...

Federated learning (also known as collaborative learning) is a sub-field of machine learning focusing on settings in which multiple entities (often referred...

Deep learning is the subset of machine learning methods based on neural networks with representation learning. The adjective "deep" refers to the use of...

In machine learning, support vector machines (SVMs, also support vector networks) are supervised max-margin models with associated learning algorithms...

of machine learning in earth sciences include geological mapping, gas leakage detection and geological features identification. Machine learning (ML)...

Unsupervised learning is a method in machine learning where, in contrast to supervised learning, algorithms learn patterns exclusively from unlabeled data...

which a machine learning model "learns". In the adaptive control literature, the learning rate is commonly referred to as gain. In setting a learning rate...

Force control is the control of the force with which a machine or the manipulator of a robot acts on an object or its environment. By controlling the contact...

Deep reinforcement learning (deep RL) is a subfield of machine learning that combines reinforcement learning (RL) and deep learning. RL considers the problem...

AI (XAI), often overlapping with interpretable AI, or explainable machine learning (XML), either refers to an artificial intelligence (AI) system over...