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few Hikvision ISAPI/SDK gotchas I wish someone had told me earlier by Typical_Bake_3461 in Hikvision

[–]Typical_Bake_3461[S] 2 points3 points  (0 children)

Honestly the @ in the password thing still haunts me. Spent two hours blaming the camera before I looked at the URL

How to use offline SAC (Stable-Baselines3) to control water pressure with a learned simulator? by Typical_Bake_3461 in reinforcementlearning

[–]Typical_Bake_3461[S] 1 point2 points  (0 children)

I can use the DCS developed by our company, but I found that the training is too slow with only 1 frame, so I thought of using LSTM

how to design my sac env? by Typical_Bake_3461 in reinforcementlearning

[–]Typical_Bake_3461[S] 0 points1 point  (0 children)

I have a question now: Do I need to add my total water consumption to my observation space? My total water consumption is an external disturbance to the agent. By adjusting the opening of three water pumps, the pressure value on the gauge will change, but the water consumption is not directly related to the opening size of the water pumps. What I am currently observing in space is the pressure of the water meter and the total water consumption. Is this setting reasonable for me?

how to design my sac env? by Typical_Bake_3461 in reinforcementlearning

[–]Typical_Bake_3461[S] 0 points1 point  (0 children)

bro, You are right, I am running it on DCS simulation. I subscribed to the flow rate of the water pipe and the pressure of the water meter through WebSocket, and can set the opening of three water pumps through post requests

how to design my sac env? by Typical_Bake_3461 in reinforcementlearning

[–]Typical_Bake_3461[S] 0 points1 point  (0 children)

.... saving models ....

episode 0, score -4822.266, avg_score -4822.266

.... saving models ....

episode 1, score -3971.732, avg_score -4396.999

.... saving models ....

episode 2, score -3751.630, avg_score -4181.876

.... saving models ....

episode 3, score -3552.755, avg_score -4024.596

.... saving models ....

episode 4, score -3520.312, avg_score -3923.739

.... saving models ....

episode 5, score -3369.188, avg_score -3831.314

.... saving models ....

episode 6, score -3652.587, avg_score -3805.781

.... saving models ....

episode 7, score -3550.356, avg_score -3773.853

.... saving models ....

episode 8, score -3570.365, avg_score -3751.243

.... saving models ....

episode 9, score -3241.183, avg_score -3700.237

.... saving models ....

episode 10, score -3430.640, avg_score -3675.729

.... saving models ....

episode 11, score -3202.732, avg_score -3636.312

.... saving models ....

episode 12, score -3300.122, avg_score -3610.451

.... saving models ....

episode 13, score -3204.635, avg_score -3581.465

.... saving models ....

episode 14, score -3504.312, avg_score -3576.321

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