TDR State Machine
Defines the operational states of a monitored system and the rules governing transitions between them. Ensuring responses to resilience loss occur in a structured, predictable, and auditable manner.
Purpose
The TDR State Machine defines the operational states of a monitored system and the rules governing transitions between them.
While the Trigger Catalogue specifies the conditions that activate alerts, the State Machine determines how the system behaves once those triggers are activated.
Its purpose is to ensure that responses to resilience loss occur in a structured, predictable, and auditable manner.
Position in the Architecture
Within the TDR–TFP architecture, the state machine operates after triggers are identified.
The state machine converts signals into operational regimes.
Conceptual Foundation
The state machine is inspired by systems engineering and safety-critical infrastructure management.
Many complex systems operate under different states depending on system stress. Examples include:
The TDR framework adopts a similar logic.
Instead of relying on discretionary intervention, the system moves between predefined states when measurable conditions are satisfied.
System States
The TDR framework uses four primary operational states.
The system operates within its Safe Operating Space.
Characteristics:
At this stage the system shows no statistically significant signal of resilience loss.
The system begins to show early signs of stress or resilience erosion.
Characteristics:
The purpose of this state is preventive stabilization.
The system is approaching a critical threshold and immediate precautionary measures are required.
Characteristics:
In this state the system shifts from growth logic to preservation logic.
The system has entered a zone of severe resilience loss or imminent systemic failure.
Characteristics:
This state represents the most severe level of prudential response.
Transition Logic
Transitions between states occur when trigger conditions are met.
Typical transitions include:
Reverse transitions are also possible when system indicators improve:
Transitions are not instantaneous but depend on: trigger activation, persistence of signals, and confirmation through calibrated indicators.
Persistence and Confirmation
To avoid excessive sensitivity to noise, transitions usually require confirmation conditions, such as:
These mechanisms ensure that the state machine responds to genuine system dynamics rather than short-term fluctuations.
State Memory
The state machine also retains memory of previous states.
This prevents rapid oscillation between states when systems fluctuate around thresholds.
Examples:
State memory improves system stability and policy credibility.
Interaction with Financial Architecture
State transitions can activate financial mechanisms within the Reversibility Finance Layer.
Institutional Integration
The state machine does not operate in isolation.
It connects directly with:
Through this integration, scientific detection of resilience loss becomes capable of producing structured institutional action.
Sector Adaptation
While the general structure of the state machine remains constant, sector-specific implementations may adjust:
For example:
The architecture remains constant, while operational parameters vary.
Objective
The objective of the TDR State Machine is to transform resilience diagnostics into structured operational regimes.
By defining system states and transition rules in advance, the framework reduces uncertainty about how institutions should respond when systems approach critical thresholds.
It ensures that responses to systemic stress are timely, predictable, and proportionate.