A research paper and demo system (developed by Stanford researchers) that demonstrates how large language models can drive simulated, human-like agents in an interactive sandbox. The project pairs LLM-based action and dialogue generation with a structured memory architecture (episodic memory, retrieval, and reflection) and simple planning to produce coherent multi-turn behavior, task execution, social interaction, and memory-driven responses; outputs are agent actions, utterances, and memory records.