ai-liquidity-in-player-markets opportunity asserted
AI liquidity in player markets
Keep player-driven markets liquid on small servers with model-driven traders whose behavior is calibrated to human trading and constrained by market rules.
thesis
Player-driven economies need large populations; EVE Online works because it has them, and smaller persistent worlds stagnate. Agents calibrated to human trading behavior, and analyzed with mean-field methods for stability, can supply liquidity and price discovery without dominating. Mechanism design keeps them from front-running humans.
design sketch
Each market has a population of agent traders with budgets, risk profiles, and information limits matching human traders, operating under the same order-book rules. Their share of volume is capped and published. Designers tune agent populations to target liquidity and volatility bands.
validation experiment
Simulate a 200-player market with and without calibrated agents using logged order data from a public game economy; measure spread, depth, volatility, and human profit share. Success: tighter spreads and lower volatility with human profit share unchanged within 5 percent.
key risks
- Players perceive bots as unfair competition.
- Agents can be exploited for arbitrage.
- Calibration drift as the human population changes.
falsifiable prediction
A persistent online game will add AI traders to its player-driven market, with their behavior fitted to observed player trading.
Announced or shipped after 2026-10-24 in a persistent online game with a player-driven market; developer material states that AI market participants were trained or calibrated on player trade data. NPC vendors with fixed prices do not count.