Edge AI reinforcement learning.

Hi technicians,

I be in my graduation semester and did sign up for a exploration project on Edge AI reinforcement learning. When I did dive into the literature I did discover that there are not so much resources out there. So to gain some knowledges and some point of views I want to share with you this technique and put some questions in this chat hopefully you can challenge me and give me some new insights :). Thank you for your time

1. Can reinforcement learning and Edge AI be easily combined? What challenges do you foresee in doing so?

2. My research suggests that this technique is particularly suitable for autonomous robotics. In your opinion, which applications are most appropriate for Edge AI combined with reinforcement learning?

3. Are there scenarios where this technique could be used for decision‑making based on sensor data, audio, or visual input?

4. Is this technique feasible on low‑MCU or high‑MCU devices?

5. Is deep Q‑learning possible on hardware devices? Most controllers that run Edge AI do not perform training directly on the device itself.

6. Do you know where I can find useful literature or libraries related to this technique?

7. Is Edge AI combined with reinforcement learning a technique that will remain relevant and valuable for the future of AI?

8. What could be interesting research questions for the topic of Edge AI reinforcement learning?