vault backup: 2025-07-31 10:18:54

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Dane Sabo 2025-07-31 10:18:54 -04:00
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"Security": 308,
"Systematic-mapping-study": 309,
"InFirstPaks": 310,
"Formal-Methods": 311
"Formal-Methods": 311,
"admin": 312
},
"_version": 3
}

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---
---
# Today's Journal
# 2025-07-30
## Morning Brief
Today's goal is to finish writing up some thesis ideas. I

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---
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# 2025-07-31
## Morning Brief
Yesterday I wrote 2 thesis ideas and started a third. Today,
we finish them! I'm struggling to write outcomes but we'll
get there over time. I can do this.
I started the morning with an hour of doomscrolling. I
really have to sort that out.
Tasks are the same from [[2025-07-30|yesterday]]. Maybe I
should make a centralized page for tasks.
- [ ] Make task page #admin
## Lunch Brief
## Note for tomorrow

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___________________________________________________________
## **Temporal Logic Specifications for Autonomous Controller Shield Synthesis**
(3)
### Goals:
### Outcomes:
### Impact:
### Related Papers:
___________________________________________________________
## **Formally Verified Runtime Monitoring and Fallback**
### Goals:
If this research is successful, we will be able to generate
autonomous controllers that provably adhere to specifications
autonomous controller shields that provably adhere to specifications
written with temporal logic automatically.
### Outcomes:
- Create an intermediary shield that mediates signals between an
optimal control system and the physical plant
optimal control system and the physical plant (MODBUS)?
-
- Translate specifications in a language like TLA+ into an
executable program
- Provide proof artifacts that automatically generated
shield components will not allow an arbitrary controller to
reach an unsafe state.
### Impact:
Shielding is one of the preeminent ways to do safe machine
learning controllers. Instead of putting the proof burden on
the machine learning component, shielding creates a safe
boundary in the state space where a safety controller will
step in if the machine learning controller endangers the
system. This technology solves a critical problem with high
assurance systems: high assurance systems have critical
safety requirements that make scrutiny on autonomous systems
safety intense. Shielding can provide a safety barrier for
the controller, allowing the architecture of the control
laws to be amenable to more efficient machine learning based
methods. Finally, utilizing an automatic translation from a
temporal logic formulation of a speculation will allow the
engineers of these systems to quickly and clearly implement
a shield, without all of the cumbersome derivation.
### Related Papers:
[[on-using-real-time-reachability-for-the-safety-assurance-of-machine-learning-controllers]]
[[enhancing-cyber-physical-system-dependability-via-synthesis-challenges-and-future-directions]]
[[safe-reinforcement-learning-via-shielding]]
___________________________________________________________
## **Formally Verified Runtime Monitoring and Fallback**
(4)
### Goals:
### Outcomes:
### Impact:
### Related Papers:
___________________________________________________________