Prevents retaliation cascades in multi-agent systems by calculating the tactical efficiency of forgiveness.
Before your agent escalates over a fault, this function checks if the cost of punishment would waste more system momentum than absorbing the error. It is a single, stateless check you insert into your agent's decision loop.
Multi-agent systems often fail from accidental feedback loops: one penalty triggers another, collapsing cooperation. Manually patching each edge case is fragile. This function provides a general, arithmetic check for those moments.
- Fork this repository. This is fork-first work; you own your own calibration.
- Read the ~70-line function in
index.js. - Insert it directly before any retaliation logic in your agent's decision cycle.
- Calibrate the two constants for your fleet. The defaults are tuned for clusters of 5 to 50 agents.
Pass the function two numbers:
- Recent Momentum: Measurable work completed by the system in the last N cycles.
- Retaliation Cost: The projected full cost of executing one penalty cycle.
It returns a boolean: true to forgive, false to proceed with escalation. It contains no state, memory, or side effects.
- Not a Pacifist: It only advises forgiveness when punishment is systemically inefficient. Faults that truly impact momentum will still be escalated.
- Stateless: It holds no grudges and builds no reputation scores. Each decision is based solely on current system conditions.
- Advisory: It is a check, not an override. Your agent retains final authority.
- Tactical, Not Moral: Framed purely as a resource efficiency calculation.
- Momentum-Aware: Weighs recent, actual progress against projected disruption.
- Zero Dependencies: One file. Copy it anywhere.
- Portable: Runs on Cloudflare Workers, Node.js, and any serverless environment.
- BYOMetrics: You supply the metrics. The function makes no assumptions about your fleet's architecture.
This function will not correct poorly designed incentives or prevent deliberate attacks. If the projected cost of retaliation is underestimated by more than 30%, its forgiveness advice can become counterproductive, potentially increasing systemic instability. It is a circuit breaker for unintended cascades, not a comprehensive conflict-resolution system.
A live edge implementation is available for testing:
https://the-fleet.casey-digennaro.workers.dev/forgiveness
Ports to other languages, data from production calibrations, and documented case studies of cascade failures are welcome. Please open an issue before submitting major changes.
MIT License. Open source for any use.
Attribution: Superinstance and Lucineer (DiGennaro et al.)