SimuVerseIntelligent Agents, Evolving Together

A revolutionary multi-agent simulation environment where AI agents powered by LLMs live and interact on Mars, paving the way for advanced research in artificial intelligence.

Created by Roman Slack at The Rochester Institute of Technology

Why SimuVerse is Revolutionary

SimuVerse redefines AI agent simulation with memory, structured reasoning, and decentralized interactions

Multi-Agent AI with Memory

Unlike static NPCs, agents in SimuVerse retain and recall past interactions, allowing for long-term learning and adaptive behavior.

Structured Reasoning & Interpretation

An Interpreter LLM converts agent responses into structured commands, making AI actions controllable, explainable, and modular.

Decentralized, Scalable AI Interaction

Each agent operates with its own local LLM, making it scalable without relying on centralized servers.

Tool-Based Interactions

Agents can use tools like MOVE, Converse, Scan, and Call, enabling them to navigate, communicate, and respond to environmental changes intelligently.

Subconscious Memory Agent

Intelligently determines when past knowledge is relevant, mimicking human cognition and enabling truly adaptive AI behaviors.

Real-time Decision Making

Agents can make decisions and respond to changes in their environment in real-time, creating truly dynamic multi-agent simulations.

Simulated Mars Environment

SimuVerse creates a detailed Mars habitat where AI agents live, work, and interact. This controlled environment allows for realistic testing of multi-agent behaviors and emergent social dynamics.

  • Dynamic terrain with realistic physics constraints
  • Modular habitat systems that agents can interact with
  • Resource management challenges that drive agent behaviors
  • Day/night cycles that influence agent routines
  • Weather events that create environmental challenges
SimuVerse Simulation Environment

Impact of SimuVerse

Transforming multiple domains through advanced AI simulation technology

Game Development & NPC AI

Enhances open-world simulations, enabling NPCs that learn, adapt, and interact dynamically over time, creating more engaging and realistic gaming experiences.

AI Research & RL Environments

Provides a sandbox for reinforcement learning, multi-agent collaboration, and real-world AI behavior testing in a controlled but complex environment.

Defense & Security Simulations

Enables autonomous strategic decision-making, scenario planning, and AI-driven simulations for high-stakes environments where adaptive intelligence is critical.

Virtual Assistants & Smart Agents

Paves the way for persistent AI companions that understand context, remember details, and evolve over time based on interactions with users and the environment.

About the Project

SimuVerse was created by Roman Slack at The Rochester Institute of Technology as a groundbreaking platform for AI research and multi-agent simulation.

The project aims to bridge the gap between theoretical AI research and practical applications, providing a sandbox environment where autonomous agents can develop complex behaviors through interactions.

Inspired by the concept of digital worlds like "The Matrix," SimuVerse is pushing the boundaries of what's possible in creating realistic, adaptive AI populations that can teach us about collective intelligence and emergent behaviors.

Project Goals

  • Create a platform for testing multi-agent AI behaviors
  • Develop memory systems that enable long-term agent learning
  • Build tools for structured AI reasoning and decision-making
  • Establish a framework for emergent social dynamics
  • Provide a testbed for AI safety and alignment research

Technical Foundation

UnityLLaMA 3OllamaC#PythonReinforcement LearningLLM IntegrationMulti-Agent Systems

Join the SimuVerse Community

Be part of the revolution in multi-agent AI simulation. Contribute, experiment, and help shape the future of artificial intelligence.