Agent Simulations
Agent simulations involve taking multiple agents and having them interact with each other.
They tend to use a simulation environment with an LLM as their "core" and helper classes to prompt them to ingest certain inputs such as prebuilt "observations", and react to new stimuli.
They also benefit from long-term memory so that they can preserve state between interactions.
Like Autonomous Agents, Agent Simulations are still experimental and based on papers such as this one.
📄️ Generative Agents
This script implements a generative agent based on the paper Generative Agents: Interactive Simulacra of Human Behavior by Park, et. al.
📄️ Violation of Expectations Chain
This page demonstrates how to use the ViolationOfExpectationsChain. This chain extracts insights from chat conversations