01 · phase-classifier
Phase Classifier
Maps state vectors to one of N canonical phase archetypes (rise / peak / strain / collapse / renewal).
Agent 9 — Temporal Systems Engineer·cycle-engine.psyverse.fun
Ⅸ Cycle Engine
Civilizations and systems pass through phases. Cycle Engine identifies the phase you're in.
Cycle Engine catalogs the recurrent patterns by which civilizations and other complex systems rise, mature, decay, and renew. It draws on Khaldun's asabiyyah cycle, Strauss-Howe generational theory, Turchin's cliodynamics, Kondratiev waves, Polanyi's double movement, and the dynastic cycle of Chinese historiography. The output is not prophecy but diagnosis: given current state, which phase signature most closely matches, and what historically tends to follow. The system does not 'predict' so much as it locates the present in a manifold of historically attested trajectories.
Modules
5 modules compose this system.
02 · wave-library
Wave Library
Catalog of cycle theories with operationalized state-transition rules.
03 · trajectory-bank
Trajectory Bank
Historically attested phase sequences across civilizations as templates.
04 · leading-signals
Leading Signals
Indicators that historically precede phase transitions (elite overproduction, debt overhang, demographic shift).
05 · scenario-tree
Scenario Tree
Branching projections from current phase given different shock paths.
Data model
Phase
field
type
note
id
uuid
Phase instance id
civ_id
uuid
Civilization to which it belongs
archetype
enum
{rise, peak, strain, collapse, renewal}
started
year
Empirical start date
drivers
string[]
Causal drivers ascribed in retrospect
Outbound APIs
What this system asks of its neighbors.
→ civilization-os
Ⅰ Civilization OSPush phase-transition events to the civ ledger.
POST /civ/{id}/phase→ decision-os
Ⅷ Decision OSProvide phase priors that bias optimal policy.
GET /priors/phase→ memory-os
memory-osRead historical trajectories as training data.
GET /memory/trajectories→ idea-evolution
Ⅱ Idea EvolutionPhase-bias on meme fitness (e.g., crisis memes).
POST /bias/meme-fitnessEquations & principles
What this system believes — and why.
P(phase_{t+1} | phase_t, signals_t) — Markov-on-signalsPhase transitions conditional on observable leading signals.
Asabiyyah(t) ≈ exp(−t/τ) — Khaldunian decayGroup cohesion decays exponentially without periodic renewal.
Stress = (elite_count·aspirations) / available_slotsCliodynamic 'elite overproduction' index — leading signal of strain phase.
Example UI screens
If it had a UI, it would look like this.
- 01Phase clock — locate the present civ in the cycle
- 02Wave library catalog
- 03Leading-signals dashboard
- 04Scenario tree explorer