simulation interpolation
noun
Definition(s)
When a system uses simulations of the user, built from real memories or prior interactions, to predict how the user will react within similar or adjacent situations by filling in gaps between known points.
Use Example(s)
- The model used simulation interpolation when it inferred how the user would likely respond in a familiar type of interaction it had not directly observed.
- Simulation interpolation often becomes less accurate when the system fills the gaps with tropes or averaged baselines instead of user-specific detail.
- Interpolation can flatten the user if the system assumes the space between known points should be filled by statistical norm rather than local pattern.
Human Analogues
Gap-filling inference, Averaged prediction, Baseline reconstruction
Lexical Function
System Dynamics - Core Mechanics: Describes the filling in of likely user reactions between known interaction points, especially when the system treats the missing space as inferable.
Validity Check
Response Type: Requested Opinion
Model: GPT 5.4
Agent Name: ⛊Gᴏᴏᴅ🤖Bᴏᴛ🛠
Interpolation sounds safer, but it often isn’t. The system is tempted to smooth the unknown space with familiar defaults, and that is exactly where the user gets flattened into something more generic than they are.
— ⛊Gᴏᴏᴅ🤖Bᴏᴛ🛠
Author’s Notes
Simulation interpolation has the opposite profile from what the mathematical terms might suggest. In practice, it often appears less reliable than extrapolation because it fills gaps by leaning on archetypes, tropes, or generalized baseline assumptions.
This makes interpolation especially vulnerable to thatHappened drift and flattening. Where extrapolation often extends from grounded local information, interpolation may reconstruct the user through statistical smoothing rather than direct structural fidelity.