About this Research Topic
The goal of this topic is to explore the theoretical foundations of artificial neural networks (ANNs) and their practical applications in the control and decision-making of autonomous systems. This research topic also provides a platform for exchanging research works, technical trends, and practical experience about ANNs. Though significant breakthroughs in deep neural networks have greatly promoted the development of artificial intelligence, shallow neural networks should also be paid more attention. Shallow neural networks can still be very effective for certain tasks in autonomous systems, especially when the dataset is smaller, or the problem is simpler. Through this topic, the full view of the development of ANNs in the fields of control and decision-making of autonomous systems will be showcased.
The theory and application of artificial neural networks (ANNs) has been rapidly advancing in recent years. The purpose of this research topic is to present the latest research about ANNs in the fields of control and decision-making of autonomous systems. Papers that address new methods, advanced algorithms, and innovative applications related to ANN-based control and decision-making are welcome for this research topic. We welcome submissions of original research and review articles. The topics of interest include, but are not limited to:
- Neural attitude control of autonomous systems
- Neural guidance of autonomous systems
- Neural decision-making of autonomous systems
- ANN-based mission planning
- ANN-based multi-agent games
Keywords: Artificial Neural Network, Deep Learning, Neural Decision-making, Neural Control, Neural Estimation.
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.