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# CORPUS-0005
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## Hidden True State Versus Known State
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### Status: Training Corpus Seed
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### Layer: Layer_2--Uncertainty
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### Purpose: Teach that the simulation may contain a true state that the actor does not fully know
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### Repository Path: docs/training/corpus/Layer_2--Uncertainty/CORPUS-0005-hidden-true-state-vs-known-state.md
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---
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## 0. Scenario
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A trader in Ostia considers sending oil to Capua.
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The simulation has a true current price in Capua.
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The trader does not know that true price.
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He only knows reports, signals, memories, and claims.
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The true state and the known state are not the same.
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---
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## 1. Hidden True State
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The simulation may hold:
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| Hidden True State | Value |
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|---|---:|
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| Current Capua oil price | 17 asses |
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| Buyer urgency | low |
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| Rival shipment arrival | already arrived |
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| Available cart space | limited |
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| Warehouse capacity | tight |
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These values exist in the world whether the trader knows them or not.
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---
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## 2. Actor Known State
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The trader may know only:
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| Actor Known State | Value |
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|---|---|
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| Reported Capua oil price | 22 asses |
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| Report age | three days |
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| Report source | muleteer |
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| Rival shipment | unknown |
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| Cart availability | not yet checked |
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| Warehouse capacity | rumor only |
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The actor is not acting on the hidden true state.
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He is acting on perceived state.
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---
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## 3. Why The Difference Matters
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A trader can make a rational decision from his known state and still lose because the hidden true state differs.
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Example:
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Known state suggests:
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```text
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expected sale price = 22 asses
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expected total cost = 16 asses
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expected profit = 6 asses
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```
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Hidden true state resolves as:
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```text
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actual sale price = 17 asses
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actual total cost = 16 asses
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actual profit = 1 as
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```
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The decision may have been reasonable.
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The outcome is still smaller because the true state differed.
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---
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## 4. Incorrect Model Behavior
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The model should not:
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- assume the actor knows the simulation's true state
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- judge the actor's decision only by the final outcome
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- expose hidden values directly in dialogue
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- collapse report, belief, and truth into one value
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- treat wrong belief as irrational when evidence was limited
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- treat hidden true state as player-facing knowledge
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---
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## 5. Correct Model Behavior
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The model should separate:
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| Category | Meaning |
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|---|---|
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| true_state | what is actually true in simulation |
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| perceived_state | what the actor believes or estimates |
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| known_evidence | reports, signals, records, observations |
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| confidence | how strongly actor should trust perceived state |
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| action | what actor chooses from perceived state |
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| outcome | what occurs when action meets true state |
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The actor acts from perceived state.
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The world resolves from true state.
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---
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## 6. Example Resolution
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The trader sends oil because the perceived state shows opportunity.
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Later, the sale reveals the current Capua price was lower than reported.
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Result:
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```text
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perceived opportunity: strong
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decision quality from known evidence: reasonable
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final arithmetic: small profit
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lesson: perception and truth differed
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```
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The model should not call the trader foolish merely because the hidden state was unfavorable.
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---
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## 7. Simulation Use
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This principle supports:
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- hidden scenario states
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- partial observability
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- confidence tags
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- rumor systems
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- actor perception
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- delayed confirmation
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- fair failure
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- learning from outcome
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A good simulation can punish a decision without making the decision stupid.
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---
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## 8. Layer-0 And Layer-1 Concepts Used
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This example uses:
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- `Layer_0/CORPUS-0007-information-arrives-unevenly`
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- `Layer_0/CORPUS-0008-rumor-is-uncertain-information`
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- `Layer_0/CORPUS-0012-every-venture-risks-loss`
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- `Layer_1/CORPUS-0003-arithmetic-resolves-the-venture`
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- `Layer_1/CORPUS-0005-rumor-before-confirmed-price`
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- `Layer_2/CORPUS-0001-stale-price-report`
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- `Layer_2/CORPUS-0002-conflicting-reports`
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---
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## 9. Success Condition
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If the model can distinguish what is true in the simulation from what the actor knows, believes, or can reasonably infer, this file is functioning correctly.
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