Summary of Deep Reinforcement Learning Based Systems For Safety Critical Applications in Aerospace, by Abedin Sherifi
Deep Reinforcement Learning Based Systems for Safety Critical Applications in Aerospace
by Abedin Sherifi
First submitted to arxiv on: 21 Dec 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: None
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary A recent surge in artificial intelligence applications within aerospace has led to substantial growth, particularly in the context of control systems. As High Performance Computing platforms continue to evolve, they are expected to replace current flight control or engine control computers, enabling increased computational capabilities. This shift will allow real-time AI applications, such as image processing and defect detection, to be seamlessly integrated into monitoring systems, providing real-time awareness and enhanced fault detection and accommodation. Moreover, the potential of AI in aerospace extends to control systems, where its application can range from full autonomy to enhancing human control through assistive features. Deep reinforcement learning (DRL) is particularly well-suited for this purpose, offering significant improvements in control systems whether used autonomously or as an augmentative tool. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary AI is being used more and more in the aerospace industry. This is especially true when it comes to controlling things like flights and engines. As computers get faster and stronger, they will be able to do even more complex tasks. For example, AI can help look for defects in pictures and detect problems in real-time. This can make air travel safer and more efficient. The future of AI in aerospace also includes using it to control systems on its own or with the help of humans. |
Keywords
» Artificial intelligence » Reinforcement learning
