From c6490ee2754a4c35ef78254926fa794e3cd4b028 Mon Sep 17 00:00:00 2001
From: Dane Sabo <dane.sabo@pitt.edu>
Date: Tue, 22 Jul 2025 11:36:46 -0400
Subject: [PATCH] vault backup: 2025-07-22 11:36:46

---
 ...A systematic review and research agenda.md | 24 +++++++++++++++++++
 ... Assurance Using Reinforcement Learning.md | 14 +++++++----
 2 files changed, 33 insertions(+), 5 deletions(-)
 create mode 100644 Notes on Papers/Economics and finance of Small Modular Reactors- A systematic review and research agenda.md

diff --git a/Notes on Papers/Economics and finance of Small Modular Reactors- A systematic review and research agenda.md b/Notes on Papers/Economics and finance of Small Modular Reactors- A systematic review and research agenda.md
new file mode 100644
index 00000000..79e086b2
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+++ b/Notes on Papers/Economics and finance of Small Modular Reactors- A systematic review and research agenda.md	
@@ -0,0 +1,24 @@
+# First Pass
+**Category:** 
+Soapbox kinda paper.
+
+**Context:** 
+Robert Woods is a professor at the University of Tennessee who previously was 
+a senior researcher at Oak Ridge National Laboratory. 
+**Correctness:** 
+**Contributions:** 
+**Clarity:** 
+
+# Second Pass
+**What is the main thrust?**
+
+**What is the supporting evidence?**
+
+**What are the key findings?**
+
+# Third Pass
+**Recreation Notes:**
+
+**Hidden Findings:**
+
+**Weak Points? Strong Points?**
diff --git a/Notes on Papers/Runtime Safety Assurance Using Reinforcement Learning.md b/Notes on Papers/Runtime Safety Assurance Using Reinforcement Learning.md
index fa2a4ede..a387a033 100644
--- a/Notes on Papers/Runtime Safety Assurance Using Reinforcement Learning.md	
+++ b/Notes on Papers/Runtime Safety Assurance Using Reinforcement Learning.md	
@@ -9,19 +9,23 @@ Drones
 
 **Correctness:** 
 Not very. They do really well in the intro and methodology, but shit hits the fan
-when it comes to the results.
+when it comes to the results. They don't explain things well, and also don't 
+really establish why their learned boundary between nominal and recovery
+controllers should be successful.
 
 **Contributions:** 
 The biggest contributions these guys make is demonstrating feasibility of their 
+reinforcement learned switching from the recovery controller and the nominal 
+controller.
 
 **Clarity:** 
+Well written until the whole thing came apart at the end.
 
 # Second Pass
-**What is the main thrust?**
+I read this a second time but I don't think it's worth it.
 
-**What is the supporting evidence?**
-
-**What are the key findings?**
+Their main contribution is trying to use RL to learn when to switch to a 
+recovery controller. 
 
 # Third Pass
 **Recreation Notes:**