Awesome resource, in case someone is interested I implemented most of suttons book here https://github.com/ivanbelenky/RL
Mathematical Foundations of Reinforcement Learning
11–20 of 46 posts
Re: Mathematical Foundations of Reinforcement Learning
#12Earlier quoted context omitted.
His books tend to be dry and geared towards researchers, in my opinion. He has a new one on RL: https://web.mit.edu/dimitrib/www/RLCOURSECOMPLETE%202ndEDITI...
I'm looking for content (researcher myself) -- mainly on the application side. Should I start with this one? Or anything else? Very curious about RL for LLMs for example (using data from real use).
I have not read it but it looks like a comprehensive reference. For a more applied treatment see Foundations of Deep Reinforcement Learning. https://slm-lab.gitbook.io/slm-lab/publications-and-talks/in...
Neither cover LLMs. I don't follow the literature closely so I can only suggest you read papers: https://github.com/WindyLab/LLM-RL-Papers
Re: Mathematical Foundations of Reinforcement Learning
#13The best lectures on Reinforcement Learning and related topics are by Dimitris Bertsekas: https://web.mit.edu/dimitrib/www/home.html
No. They are outdated and focused on strange things. You wont understand ppo from his textbooks
Re: Mathematical Foundations of Reinforcement Learning
#14Re: Mathematical Foundations of Reinforcement Learning
#15I don't know how to go from understanding this material to having a job in the field. Just stuck as a SWE for now.
Re: Mathematical Foundations of Reinforcement Learning
#16I don't know how to go from understanding this material to having a job in the field. Just stuck as a SWE for now.
- Do you understand the material?
- Can you utilize your understanding to build successful models/algorithms?
A way I like to gauge someone's understandings of things is by getting them to explain the limitations. This is often less explicitly stated in learning and a deeper understanding is acquired through experience and most importantly, reflection on that experience. This is often an underutilized tactic but it is very effective. If you can't do this, then the good news is that starting now will only accelerate your understanding :)
Re: Mathematical Foundations of Reinforcement Learning
#17I don't know how to go from understanding this material to having a job in the field. Just stuck as a SWE for now.
- Do you understand the material? - Can you utilize your understanding to build successful models/algorithms? If the answer is yes to both, do some projects, put them on your github, and update your resume. You might need to take a job at a lower position first, but you can jump from there. But I want to make sure that the answer is "yes" to both and note that it is easy to think you understand something without actu…
Just a random thought:
Understanding the limitations is a complicated thing in tech. You can finnangle most systems into doing mostly anything, as inefficient as that may prove to be.
The question then becomes up to what point is it "a reasonably better than most others" solution. And that's a question of an understanding of a field, not a space in the field.
Re: Mathematical Foundations of Reinforcement Learning
#18Highly recommended .. even the main contents diagram is a great visual overview of RL in general, as is the 30 minute intro YT video.
Im expecting to see a lot of hyper growth startups using RL to solve a realworld problem in engineering / logistics / medicine
LLMs currently attract all the hype for good reasons, but Im surprised VCs dont seem to be looking at RL companies specifically.
Re: Mathematical Foundations of Reinforcement Learning
#196-lecture series on the Foundations of Deep RL by Pieter Abbeel is also very recommended. gives very good overview and intuition
https://youtu.be/2GwBez0D20A
Re: Mathematical Foundations of Reinforcement Learning
#20I don't know how to go from understanding this material to having a job in the field. Just stuck as a SWE for now.
- Do you understand the material? - Can you utilize your understanding to build successful models/algorithms? If the answer is yes to both, do some projects, put them on your github, and update your resume. You might need to take a job at a lower position first, but you can jump from there. But I want to make sure that the answer is "yes" to both and note that it is easy to think you understand something without actu…
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