Generative Agents and Emergent Simulation

Park et al. 2023 (UIST '23, arXiv:2304.03442) populated **Smallville**, a sandbox of 25 agents, with a three-part architecture: **memory stream** (natural-language log), **reflection** (higher-level syntheses the agent generates about its own stream), and **plan** (day-level behavior, then sub-plans). The landmark result was the Valentine's Day party emergence: one agent seeded with "wants to throw a Valentine's Day party," without further scripting, produced invitations spread through the population, coordinated dates, and the party happened — from 24 agents who started with no knowledge of it. Ablations show all three components are required for believability. The documented failures are spatial-norm errors (entering closed stores, sharing single-person bathrooms). This is the reference architecture for agent simulations and multi-agent social evaluation in 2026.