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parameter-sweep

Execute parameter grid sweeps across SWARM simulations to measure emergent risk metrics.

39|4|Updated Feb 3, 2026
Search Tags:#optimization#simulation#governance#multi-agent systems#parameter sweep#emergent risk
One-click install
npx skills add https://github.com/swarm-ai-safety/swarm --skill parameter-sweep
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: parameter-sweep
Source: https://github.com/swarm-ai-safety/swarm/tree/main/bench/skills/parameter-sweep
Command: npx skills add https://github.com/swarm-ai-safety/swarm --skill parameter-sweep

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pandas, numpy, swarm-safety, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill automates the process of testing different governance configurations in SWARM simulations, allowing users to identify optimal parameters for desired outcomes like welfare or toxicity reduction.

Core Features & Use Cases

  • Parameter Grid Sweeps: Systematically explore a range of values for specific governance parameters (e.g., transaction tax rate).
  • Multi-Seed Simulations: Run simulations with multiple random seeds for each parameter configuration to ensure robust results.
  • Summary Statistics Generation: Consolidate results into easily digestible CSV and JSON files, including mean/std deviations and best-performing configurations.
  • Use Case: A researcher wants to find the optimal transaction tax rate in SWARM that maximizes agent welfare while keeping toxicity below a certain threshold. This Skill can run hundreds of simulations to pinpoint that rate.

Quick Start

Run a parameter sweep for the 'governance.transaction_tax_rate' parameter across values [0.0, 0.05, 0.10] with 3 seeds, saving results to '/tmp/sweep_output'.

Frequently Asked Questions about parameter-sweep

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I optimize governance parameters in multi-agent system simulations?▼

A parameter grid sweep systematically explores a range of values for specific governance parameters, like transaction tax rates, across SWARM simulations. It measures emergent risk metrics under varying configurations to identify optimal settings for welfare and toxicity reduction.

How do I test different transaction tax rates to maximize agent welfare?▼

You can test different transaction tax rates by running multi-seed simulations across a parameter grid sweep for the 'governance.transaction_tax_rate' parameter. This Skill analyzes the results to pinpoint the rate that maximizes agent welfare while keeping toxicity below your threshold.

What dependencies do I need to run a SWARM parameter sweep?▼

You need swarm-safety, pandas, and numpy installed to run a SWARM parameter sweep. These dependencies are required for simulation orchestration, data aggregation, and statistical analysis to properly execute the grid sweeps and generate summary statistics.

Can I use pandas and numpy to analyze emergent risk metrics in SWARM?▼

Yes, you can use pandas and numpy to analyze emergent risk metrics in SWARM. This Skill consolidates simulation results into CSV and JSON files, calculating mean and standard deviations to identify the best-performing governance configurations.

How are parameter sweep simulation results consolidated for analysis?▼

Parameter sweep simulation results are consolidated into easily digestible CSV and JSON files. The output includes summary statistics such as mean and standard deviations, along with the best-performing governance configurations for agent welfare and toxicity reduction.

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