AIOP Jun. 7, 2024
The current weekly meeting time is every other Monday at 13:00 US/Eastern
Connection Info:
You can connect using ZOOM Video conferencing (ID: 161 588 8669). (Click "Expand" to the right for details -->):
One tap mobile: US: +16692545252,,1602484178# or +16468287666,,1602484178#
Meeting URL: https://jlab-org.zoomgov.com/j/1615888669?pwd=MnhGVUhpeEd3NVpnTGxoZHJManNBdz09&from=addon
Meeting ID: 161 588 8669
Passcode: 561441
Join by Telephone
For higher quality, dial a number based on your current location.
Dial: +1 669 254 5252 US (San Jose)
+1 646 828 7666 US (New York)
+1 646 964 1167 US (US Spanish Line)
+1 551 285 1373 US (New Jersey)
+1 669 216 1590 US (San Jose)
+1 415 449 4000 US (US Spanish Line)
833 568 8864 US Toll-free
Meeting ID: 161 588 8669
International numbers
Join from an H.323/SIP room system
H.323: 161.199.138.10 (US West)
161.199.136.10 (US East)
Meeting ID: 161 588 8669
Passcode: 561441
SIP: 1615888669@sip.zoomgov.com
Passcode: 561441
One tap mobile: US: +16692545252,,1601987443# or +16468287666,,1601987443#
Meeting URL: https://jlab-org.zoomgov.com/j/1615888669?pwd=MnhGVUhpeEd3NVpnTGxoZHJManNBdz09&from=addon
Meeting ID: 161 588 8669
Passcode: 561441
AIOP - Polarized Photon Source
Agenda:
- Previous Meeting
- Announcements
- Project Progress
- ML Activities
- AOT
Minutes
AIOP Special Friday Meeting Notes
We should decide on a single framework for both projects
Armen has made some nice slides over this repo: SciOptControl Toolkit
Patrick’s questions:
How do we handle using a sparse data set in the offline/online environments?
Malachi — if we have a physical model, we can calibrate with historical data, then we can create the surrogate that we can wrap in openAI gym
Malachi suggests a white board meeting which is a good idea
We can try toy problems with different environments in openAI gymnasium
DS group really needs dataset summaries for each run period
David — there is a natural time scale for this, every measurement we take of the polarization is not necessarily incredibly accurate. Can we use information from more than 1 time step back? Do you have to give it a characteristic time scale or can it figure that out in the training process? Armen had an answer for this I just don't have what it was -- I think it is configurable though
Action Items
- Placeholder
Milestones!
- Identify relevant parameters
- Identify nudge events
- Shapley analysis!