vault backup: 2026-06-04 19:29:28

Running Start/CSB320 - Machine Learning Concepts/Class 6-4 (Reinforcement Learning).md

@@ -25,4 +25,6 @@
 	- assembles all possible q values on the way to end reward
 	- updates q values to find best path
 	- $$Q^{new}(s_{t}, a_{t}) \leftarrow (1 - a) * Q(s_{t}, a_{t}) + a * (r_{t} + \gamma * max_{a} Q(s_{t+1}, a))$$
-	- 
+	- ![[BellmanEquation.excalidraw]]
+	- This equation can be used to update the q values of the grid
+	- it takes the old value and adds