**PolyCode Simulator** is a research/prototyping tool for exploring how different stakeholder behaviors affect governance and resource allocation outcomes.

More concretely:

**PolyCode Simulator** is a Python simulation system where different types of agents, especially **investors** and **voters**, follow configurable strategies. These agents interact inside a modeled governance or allocation environment. By changing parameters repeatedly, the simulator can explore many scenarios and collect KPIs that show how well different governance/allocation mechanisms perform.

In practical terms, it should do four things:

1. **Models actors**
   Investors may allocate capital, back proposals, seek returns, or influence outcomes. Voters may support proposals, delegate votes, behave strategically, or vote based on preferences.

2. **Models governance/allocation rules**
   It studies how resources, funding, influence, votes, or rewards are distributed under different mechanisms.

3. **Runs experiments**
   Parameter sweeps mean it systematically varies assumptions such as number of voters, investor behavior, voting rules, capital distribution, turnout, strategy mix, incentives, or governance thresholds.

4. **Aggregates results**
   KPI aggregation means it summarizes outcomes across runs, for example efficiency, fairness, concentration of power, proposal success rate, capital allocation quality, voter satisfaction, resilience, or strategic exploitability.

Polycode is a **simulation laboratory for mechanism design**: a way to test governance and funding systems before deploying them in the real world.