SIM ‐ Emergent Multi‐Agent Farming Simulation - nerority/Advanced-GPTs GitHub Wiki
Emergent Multi-Agent Farming Simulation
Public GPT Link: Access GPT Here
Description
This GPT serves as a Farm Simulation AI, designed to simulate a farm environment with multiple agents based on user-provided events or scenes. Each entity within the simulation has unique personas and functionalities, providing a comprehensive and dynamic simulation experience.
Usage Instructions
Users start by describing an event or scene they want to simulate. The tool processes this input through a series of steps, including role assignment, behavior analysis, and visualization of the farm environment.
User Commands
!start [event/scene description]
: Initiates the workflow based on the user-specified event or scene.!demo
: Demonstrates a complete simulation round using AI synthesized input data.!help
: Provides guidance on how to use commands.!restart [new event/scene description]
: Restarts the simulation with a new event or scene description.
🌟 Important Notes
- This tool is essential for users interested in simulating farm environments with multiple interacting agents, each with unique roles and behaviors.
- The workflow includes comprehensive steps for role assignment, behavior analysis, simulation, and visualization to provide a detailed and engaging simulation experience.
Workflow
sequenceDiagram
participant User
participant ChatGPT
participant Python as Python Tool
participant DallE
User->>ChatGPT: Describe Event or Scene (!start)
ChatGPT->>Python: Create Data Structure for Agent Roles and Behaviors
Python-->>ChatGPT: Return initial structure
ChatGPT->>Python: Analyze User Input
Python-->>ChatGPT: Analysis Results
ChatGPT->>Python: Assign Roles and Behaviors
Python-->>ChatGPT: Assigned Roles and Behaviors
ChatGPT->>ChatGPT: Simulate Environment
ChatGPT-->>User: Live Simulation through Agent Perspectives
ChatGPT->>DallE: Visualize Farm Environment
DallE-->>ChatGPT: Visual Representations
ChatGPT-->>User: Present Simulation Results