marcorealacci/master-degree-notes
1
0
Fork 0
Code Issues Pull requests Projects Releases Packages Wiki Activity Actions

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

Browse source
This commit is contained in:
Marco Realacci 2024-10-24 15:52:06 +02:00
parent d1b1857d81
commit 63da6484c7
2 changed files with 17 additions and 55 deletions
Download patch file Download diff file Expand all files Collapse all files

57
.obsidian/workspace.json vendored
View file

@ -7,60 +7,22 @@
"id": "ee1680277f6a0d97",
"type": "tabs",
"children": [
{
"id": "8d8de4cd4c80f0f8",
"type": "leaf",
"state": {
"type": "markdown",
"state": {
"file": "Autonomous Networking/notes/3 WSN MAC.md",
"mode": "source",
"source": false
},
"icon": "lucide-file",
"title": "3 WSN MAC"
}
},
{
"id": "e86977f921664e81",
"type": "leaf",
"state": {
"type": "markdown",
"state": {
"file": "Autonomous Networking/notes/6 Internet of Things.md",
"file": "Autonomous Networking/notes/7 RL.md",
"mode": "source",
"source": false
},
"icon": "lucide-file",
"title": "6 Internet of Things"
}
},
{
"id": "0f6b9ae8038d6ee6",
"type": "leaf",
"state": {
"type": "image",
"state": {
"file": "Biometric Systems/images/Pasted image 20241023133231.png"
},
"icon": "lucide-image",
"title": "Pasted image 20241023133231"
}
},
{
"id": "46b435f098a3c1ca",
"type": "leaf",
"state": {
"type": "image",
"state": {
"file": "Biometric Systems/images/Pasted image 20241023133231.png"
},
"icon": "lucide-image",
"title": "Pasted image 20241023133231"
"title": "7 RL"
}
}
],
"currentTab": 3
"stacked": true
}
],
"direction": "vertical"
@ -216,10 +178,14 @@
"obsidian-git:Open Git source control": false
}
},
"active": "2b2245f56092006e",
"active": "0d5325c0f9289cea",
"lastOpenFiles": [
"Biometric Systems/images/Pasted image 20241023135125.png",
"Autonomous Networking/notes/2 RFID.md",
"Autonomous Networking/notes/7 RL.md",
"Autonomous Networking/slides/7 RL1.pdf",
"Autonomous Networking/notes/3 WSN MAC.md",
"Biometric Systems/images/Pasted image 20241023133231.png",
"Biometric Systems/images/Pasted image 20241023135125.png",
"Biometric Systems/images/Pasted image 20241023135925.png",
"Biometric Systems/images/Pasted image 20241023135127.png",
"Biometric Systems/images/Pasted image 20241023135922.png",
@ -228,20 +194,15 @@
"Biometric Systems/images/Pasted image 20241023141948.png",
"Biometric Systems/images/Pasted image 20241023144725.png",
"Biometric Systems/images/Pasted image 20241024090856.png",
"Biometric Systems/images/Pasted image 20241024091235.png",
"Autonomous Networking/notes/3 WSN MAC.md",
"Autonomous Networking/slides/2 RFID.pdf",
"conflict-files-obsidian-git.md",
"Autonomous Networking/notes/4 WSN Routing.md",
"Autonomous Networking/notes/6.1 RL.md",
"Biometric Systems/slides/LEZIONE5_NEW_More about face localization.pdf",
"Autonomous Networking/slides/7 RL1.pdf",
"Autonomous Networking/slides/6 IoT.pdf",
"Autonomous Networking/notes/7 RL.md",
"Autonomous Networking/slides/3 WSN.pdf",
"Autonomous Networking/slides/4 WSN2.pdf",
"Autonomous Networking/notes/6 Internet of Things.md",
"Autonomous Networking/notes/2 RFID.md",
"Autonomous Networking/notes/5 Drones.md",
"Biometric Systems/slides/LEZIONE4_Face introduction and localization.pdf",
"Biometric Systems/notes/4. Face recognition.md",

13
Autonomous Networking/notes/7 RL.md
View file

@ -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 state representation defines what happens next
- ...
- the history is involved in taking the next decision:
- 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: