tcai_cycle
Run recursive cycles of consciousness simulation (SNN to qualia to self-model) with early stopping when the loop reaches a stable, satisfied state.
Instructions
Run one or more ACM cycles (the_consciousness_ai port): SNN signals → AKOrN binding → GNW ignition → qualia → emotion → reward shaping → emotional memory → self-model → second-order loop. Set stopWhenSatisfied to halt early once the recursive loop reaches a sustained satisfactory (converged, low-curiosity, stable) regime.
Input Schema
TableJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| cycles | No | Number of cycles (default 1; upper bound if stopWhenSatisfied) | |
| rewardSignal | No | Task feedback ∈ [−1,1] | |
| novelty | No | Surprise/curiosity ∈ [0,1] | |
| threat | No | ||
| controllability | No | ||
| predictionError | No | World-model surprise (raw) | |
| predictionConfidence | No | ||
| narrative | No | Annotation for the memory record | |
| stopWhenSatisfied | No | Halt early when the second-order loop reports sustained satisfaction | |
| epsFreeEnergy | No | Halt threshold: absolute |ΔF| ≤ (nats, default 0.02) | |
| relFreeEnergy | No | Halt threshold: |ΔF| ≤ rel·F, scale-free (default 0.03) | |
| minTaskQuality | No | Halt threshold: realized task quality ≥ (default 0.6) | |
| maxEpistemic | No | Halt threshold: expected info gain ≤ (default 0.1) | |
| satisfactionPatience | No | Consecutive satisfied cycles required to halt (default 3) | |
| closedLoop | No | Enable closed-loop actuation (AIF action drives the substrate); default on |