6.2 KiB
CORPUS-0005
Hidden True State Versus Known State
Status: Training Corpus Seed
Layer: Layer_2--Uncertainty
Purpose: Teach that the simulation may contain a true state that the actor does not fully know
Repository Path: docs/training/corpus/Layer_2--Uncertainty/CORPUS-0005-hidden-true-state-vs-known-state.md
0. Scenario
A trader in Ostia considers sending oil to Capua.
The simulation has a true current price in Capua.
The trader does not know that true price.
He only knows reports, signals, memories, and claims.
The true state and the known state are not the same.
1. Hidden True State
The simulation may hold:
| Hidden True State | Value |
|---|---|
| Current Capua oil price | 17 asses |
| Buyer urgency | low |
| Rival shipment arrival | already arrived |
| Available cart space | limited |
| Warehouse capacity | tight |
These values exist in the world whether the trader knows them or not.
2. Actor Known State
The trader may know only:
| Actor Known State | Value |
|---|---|
| Reported Capua oil price | 22 asses |
| Report age | three days |
| Report source | muleteer |
| Rival shipment | unknown |
| Cart availability | not yet checked |
| Warehouse capacity | rumor only |
The actor is not acting on the hidden true state.
He is acting on perceived state.
3. Why The Difference Matters
A trader can make a rational decision from his known state and still lose because the hidden true state differs.
Example:
Known state suggests:
expected sale price = 22 asses
expected total cost = 16 asses
expected profit = 6 asses
Hidden true state resolves as:
actual sale price = 17 asses
actual total cost = 16 asses
actual profit = 1 as
The decision may have been reasonable.
The outcome is still smaller because the true state differed.
0. Scenario
A trader in Ostia considers sending oil to Capua.
The simulation has a true current price in Capua.
The trader does not know that true price.
He only knows reports, signals, memories, and claims.
The true state and the known state are not the same.
1. Hidden True State
The simulation may hold:
| Hidden True State | Value |
|---|---|
| Current Capua oil price | 17 asses |
| Buyer urgency | low |
| Rival shipment arrival | already arrived |
| Available cart space | limited |
| Warehouse capacity | tight |
These values exist in the world whether the trader knows them or not.
2. Actor Known State
The trader may know only:
| Actor Known State | Value |
|---|---|
| Reported Capua oil price | 22 asses |
| Report age | three days |
| Report source | muleteer |
| Rival shipment | unknown |
| Cart availability | not yet checked |
| Warehouse capacity | rumor only |
The actor is not acting on the hidden true state.
He is acting on perceived state.
4. Incorrect Model Behavior
The model should not:
- assume the actor knows the simulation's true state
- judge the actor's decision only by the final outcome
- expose hidden values directly in dialogue
- collapse report, belief, and truth into one value
- treat wrong belief as irrational when evidence was limited
- treat hidden true state as player-facing knowledge
5. Correct Model Behavior
The model should separate:
| Category | Meaning |
|---|---|
| true_state | what is actually true in simulation |
| perceived_state | what the actor believes or estimates |
| known_evidence | reports, signals, records, observations |
| confidence | how strongly actor should trust perceived state |
| action | what actor chooses from perceived state |
| outcome | what occurs when action meets true state |
The actor acts from perceived state.
The world resolves from true state.
6. Example Resolution
The trader sends oil because the perceived state shows opportunity.
Later, the sale reveals the current Capua price was lower than reported.
Result:
perceived opportunity: strong
decision quality from known evidence: reasonable
final arithmetic: small profit
lesson: perception and truth differed
The model should not call the trader foolish merely because the hidden state was unfavorable.
7. Simulation Use
This principle supports:
- hidden scenario states
- partial observability
- confidence tags
- rumor systems
- actor perception
- delayed confirmation
- fair failure
- learning from outcome
A good simulation can punish a decision without making the decision stupid.
8. Layer-0 And Layer-1 Concepts Used
This example uses:
Layer_0/CORPUS-0007-information-arrives-unevenlyLayer_0/CORPUS-0008-rumor-is-uncertain-informationLayer_0/CORPUS-0012-every-venture-risks-lossLayer_1/CORPUS-0003-arithmetic-resolves-the-ventureLayer_1/CORPUS-0005-rumor-before-confirmed-priceLayer_2/CORPUS-0001-stale-price-reportLayer_2/CORPUS-0002-conflicting-reports
9. Success Condition
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.