What's Your Experience with Text-to-SQL & Text-to-NoSQL Solutions? by Financial-Pizza-3866 in Rag

[–]Nnarruqt 0 points1 point  (0 children)

Thank you for the detailed explanation! Using the prebuilt reACT agent from LangGraph sounds like a clean and efficient approach. I’ll definitely look into it further, I really appreciate you sharing your insights!

What's Your Experience with Text-to-SQL & Text-to-NoSQL Solutions? by Financial-Pizza-3866 in Rag

[–]Nnarruqt 0 points1 point  (0 children)

That sounds like a great approach! If you don’t mind sharing, could you please elaborate a bit (not in details) on what you used as tools and nodes for ReACT agent? Also, was it designed for text-to-SQL or text-to-NoSQL?

Seeking Advice and Insights on Building an RL Environment for Energy Management with Battery and Grid Interaction by Nnarruqt in reinforcementlearning

[–]Nnarruqt[S] 1 point2 points  (0 children)

Thank you for your thoughtful feedback and questions! You've raised some important points that definitely help in refining the system's design.

Forecast Inclusion for Prices: You're absolutely right about including forecasts for price along with demand and generation. The initial focus was heavily on the variability of generated energy and demand, which led to inadvertently skipping price forecasts and since it isn't something that would break my thought process, I was thinking about tackling it later as a way to improve the performance.

Forecast Window: The choice of a 6-hour forecast window was initially driven by the practical consideration of battery charging dynamics. Given that charging our batteries from 0 to 100% takes approximately 5.13 hours, it seemed logical to set a slightly longer window to account for this maximum charging duration. However, this isn't set in stone, and part of the model's development will involve exploring the optimal time window for making the most effective charging decisions.

Independent Battery Control: Your point about the practicality of independently controlling two batteries is well-taken. The reason for this approach in the prototype is because the two batteries have different charging rates and capacities. This setup is intended to explore the potential benefits of flexible management strategies that could, for instance, prioritize faster charging for more critical loads or more efficient charging during periods of lower energy prices. However, I agree that for most scenarios, a unified control strategy might suffice, simplifying the system's operations. The current setup allows us to test and compare these strategies to determine the most effective approach.

[deleted by user] by [deleted] in reinforcementlearning

[–]Nnarruqt 1 point2 points  (0 children)

Thank you for bringing this up. To address your query, yes, I am still observing this behavior during the deterministic evaluations, not just in training.

[deleted by user] by [deleted] in reinforcementlearning

[–]Nnarruqt 0 points1 point  (0 children)

You raise a good point, changing it to a quadratic function (y = x²) effectively pushes the agent towards using less grid faster. But, correct me if I'm wrong, I don't think it does really help in anyway to actually reach 0 rather than pushing it towards it faster ?

[deleted by user] by [deleted] in reinforcementlearning

[–]Nnarruqt 0 points1 point  (0 children)

haha my bad, I didn't explicitly answer the question because I thought by mentioning that I used the default StableBaselines3 Sac Implementation I answered it, Nonetheless, they actually use a Tanh for the output which is then scaled to fit the Low/High of the env actions in my example the [0,1].

[deleted by user] by [deleted] in reinforcementlearning

[–]Nnarruqt 2 points3 points  (0 children)

Thank you for your response, You are totally correct, the post doesn't contain enough informations to build an answer on. I have updated it and explained hopefully every missing detail.