Autonomous Economy Simulator
Research ModelThe simulator stress-tests virtual economies with populations of simulated economic agents: player supply and demand, NFT pricing, resource sinks, farming and bot behavior, inflation, marketplace liquidity and token incentives. Monte Carlo sweeps over economic variables surface failure modes — death spirals, liquidity crunches, exploit-driven inflation — before a balance change ships.
- Simulated Agents
- 10M
- Market Events / Run
- 1.8B
- Monte Carlo Scenarios
- 100K+
- Token-Eq / Run
- 1.2T–4.8T
Per-run research workload — independent of the monthly global scenario.
Each run instantiates a population of heterogeneous economic agents — casual players, optimizers, market makers, botting operations — and lets them trade against a world's actual sink and faucet rules. Sweeps vary two dozen economic variables at a time; a run is judged by the distribution of outcomes, not a single trajectory.
Because runs are episodic, their workload is quoted per run rather than per month: a full Monte Carlo sweep is modeled at 1.2T–4.8T token-equivalent depending on population size and horizon, and sits outside the monthly global scenario budget.