Mind · Reasoning
CognitiveEcho
Estimating difficulty via simulation variance
Definition
Mechanism
Variance-Based Effort Estimation: Agent runs N rapid, low-fidelity simulations of the task. If outcomes diverge significantly, it triggers decomposition. Ping the problem before solving it. High variance in simulation implies hidden complexity. Process: (1) Generate N quick solution sketches, (2) Measure outcome variance, (3) If variance > threshold, decompose; else execute simplest solution.
Preconditions
- Feedback loop enabled
- Input signal
Postconditions
- Signal amplified or validated
Invariants
- Delay does not exceed short-term memory bounds
- Echo content matches input semantic hash
Risks
Failure modes
Correlated Hallucination
All simulations are wrong in the exact same way (low variance, high error).
The simulation model might be too simple to catch edge cases (false negative).
Simulation cost may exceed just trying the task for truly simple problems.
Sample count is arbitrary - tuning required.
Relationships
Builds on
References
Autonomous Goal-Directed Entity
Infrastructure
Raw information emission
A virtualized execution
Nothing in this library builds on this pattern yet.
Reference