vault backup: 2024-10-24 15:52:06

.obsidian/workspace.json

@@ -7,60 +7,22 @@
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-              "title": "6 Internet of Things"
+              "title": "7 RL"
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@@ -216,10 +178,14 @@
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+    "Autonomous Networking/notes/7 RL.md",
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+    "Autonomous Networking/notes/3 WSN MAC.md",
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     "Autonomous Networking/slides/4 WSN2.pdf",
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Autonomous Networking/notes/7 RL.md

@@ -84,12 +84,12 @@ exploration vs exploitation dilemma:
 - emits observation Ot
 - emits scalar reward Rt
 
-
-
 **agent state:** the view of the agent on the environment state, is a function of history
-- the function of the history is involved in taking the next decision
+- the history is involved in taking the next decision:
-- the state representation defines what happens next
+	- agent selects actions
-- ...
+	- environment selects observations/rewards
+- the state information is used to determine what happens next
+	- state is a function of history: $S_t = f(H_t)$
 	
 #### Inside the agent
 one or more of these components
@@ -107,9 +107,10 @@ one or more of these components
 	- is a prediction of future reward
 	- used to evaluate the goodness/badness of states
 	- values are prediction of rewards
-	- Vp(s) = Ep[yRt+1 + y^2Rt+2 ... | St = s]
+	- $V_\pi(s) = Ep[yRt+1 + y^2Rt+2 ... | St = s]$
 - **Model:**
 	- predicts what the environment will do next
+	- may predict the resultant next state and/or the next reward
 	- many problems are model free
 
 back to the original problem: