Panopticon-AI-team/panopticon
📦 Open Source ProjectPanopticon-AI-team
A specialized wargaming platform designed for training and testing reinforcement learning agents in complex tactical environments.
Panopticon serves as a dedicated engine for agent-based simulation, tailored for the unique requirements of wargaming and military-style operations research. Unlike general-purpose game engines, Panopticon is architected to facilitate reinforcement learning (RL) workflows, providing the necessary hooks and interfaces for agents to perceive state, execute actions, and receive rewards within a tactical simulation.
Key technical features include a modular framework that supports complex entity interactions, environmental constraints, and multi-agent scenarios. By utilizing TypeScript, the platform offers a type-safe environment that simplifies the integration of custom simulation logic and agent policies. It is designed to handle the intricacies of wargaming—such as fog of war, logistics, and unit attrition—making it an ideal sandbox for researchers looking to push the boundaries of autonomous strategic planning. Whether for academic research or defense-oriented modeling, Panopticon provides the infrastructure to simulate, train, and validate AI agents in high-stakes, competitive environments.
💡Highlights
- ├─TypeScript-based RL environment
- ├─Optimized for wargaming logic
- └─Supports multi-agent simulation
🎯For
- ├─AI Researchers
- ├─Operations Research Analysts
- └─Game Developers