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Marco Realacci 2024-10-24 15:52:06 +02:00
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57
.obsidian/workspace.json vendored
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@ -7,60 +7,22 @@
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15
Autonomous Networking/notes/7 RL.md
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@ -84,13 +84,13 @@ 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
- **Policy:** agent's behavior function
@ -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: