What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Machine learning
- Artificial neural network
His primary scientific interests are in Artificial neural network, Artificial intelligence, Control theory, Optimal control and Machine learning.
He studies Backpropagation which is a part of Artificial neural network.
His Artificial intelligence research is multidisciplinary, incorporating elements of Particle swarm optimization and Pattern recognition.
Donald C. Wunsch has researched Control theory in several fields, including Backpropagation through time and Electric power system.
His Optimal control research integrates issues from Voltage regulator, Reinforcement learning, Trajectory and Nonlinear system.
His study in Machine learning is interdisciplinary in nature, drawing from both Risk management and Pattern recognition.
His most cited work include:
- Survey of clustering algorithms (4319 citations)
- Adaptive critic designs (1034 citations)
- Handbook of Learning and Approximate Dynamic Programming (635 citations)
What are the main themes of his work throughout his whole career to date?
The scientist’s investigation covers issues in Artificial intelligence, Artificial neural network, Machine learning, Control theory and Cluster analysis.
Artificial intelligence and Pattern recognition are frequently intertwined in his study.
Backpropagation is the focus of his Artificial neural network research.
His Particle swarm optimization and Unsupervised learning investigations are all subjects of Machine learning research.
Control theory is closely attributed to Electric power system in his research.
His research on Cluster analysis frequently links to adjacent areas such as Data mining.
He most often published in these fields:
- Artificial intelligence (40.48%)
- Artificial neural network (40.04%)
- Machine learning (16.41%)
What were the highlights of his more recent work (between 2017-2021)?
- Artificial intelligence (40.48%)
- Cluster analysis (13.79%)
- Artificial neural network (40.04%)
In recent papers he was focusing on the following fields of study:
His primary areas of study are Artificial intelligence, Cluster analysis, Artificial neural network, Reinforcement learning and Control theory.
His Artificial intelligence research incorporates elements of Machine learning and Pattern recognition.
He combines subjects such as Negentropy, Data mining, Data visualization and Adaptive resonance theory with his study of Cluster analysis.
His research in Artificial neural network intersects with topics in Automation and Process.
His Reinforcement learning research is multidisciplinary, relying on both Observer, Transformation, Linear system and Mathematical optimization.
His Optimal control, Control theory and Nonlinear system study, which is part of a larger body of work in Control theory, is frequently linked to Algebraic Riccati equation, bridging the gap between disciplines.
Between 2017 and 2021, his most popular works were:
- Leader–Follower Output Synchronization of Linear Heterogeneous Systems With Active Leader Using Reinforcement Learning (39 citations)
- Optimal Containment Control of Unknown Heterogeneous Systems With Active Leaders (29 citations)
- Heuristic Dynamic Programming for Adaptive Virtual Synchronous Generators (27 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Machine learning
- Artificial neural network
Donald C. Wunsch mainly focuses on Reinforcement learning, Artificial neural network, Control theory, Cluster analysis and Artificial intelligence.
The various areas that Donald C. Wunsch examines in his Reinforcement learning study include Linear system and Mathematical optimization.
His study looks at the intersection of Artificial neural network and topics like Dynamic programming with State, Stability, Computer hardware and Vector control.
His work on Optimal control as part of his general Control theory study is frequently connected to Algebraic Riccati equation and Hydrogen sulfide, thereby bridging the divide between different branches of science.
Donald C. Wunsch interconnects Node, Computer network, Data visualization and Adaptive resonance theory in the investigation of issues within Cluster analysis.
His research investigates the connection with Artificial intelligence and areas like Machine learning which intersect with concerns in Social media, Representation and Software.
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