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Descendants (Core)

A Next-Generation Agentic AI Simulation Platform
Powered by Cortana Research & Development Center

Cortana Descendants Large

📖 Overview

Descendants is an advanced 3D simulation platform designed to bridge the gap between human intelligence and artificial agents. Built on a "Modular Monolith" architecture, it combines high-fidelity 3D rendering with autonomous agent logic, enabling complex interactions in a persistent virtual world.

This project represents the foundation of CortanaOS—a future operating system for spatial computing and agentic collaboration.

Demo.2.mp4
Screen.Recording.2025-12-06.at.2.15.19.AM.mov

🚀 Vision & Future

Our roadmap is driven by the convergence of Spatial Intelligence and Generative AI.

🧠 6-Layer Design Architecture

  1. Application Layer: User interfaces, Next-gen UI/UX.
  2. Communication Layer: Multi-Protocol Support (MCP), A2A (Agent-to-Agent) messaging.
  3. Intelligence Layer: Agentic AI, Large Model integration (500+ models), Adaptive Context.
  4. Spatial Layer: World Engine, Custom 3D Pipeline, Physics & Environment.
  5. Encryption Layer: Secure data handling for "Dual User" (Human & Simulant) privacy.
  6. Hardware Abstraction Layer: Cross-platform compatibility (Web, VR/AR).

🌟 Key Pillars

  • RealityLink: Seamless bridging of virtual and physical contexts.
  • Simulated Vision: Agents possess depth perception, temporal context, and simulated "senses".
  • Time-Travel: Advanced state management allowing temporal navigation of simulation states.
  • Agentic Collaboration: Simulants (AI) and Humans working together in shared spaces.

🏗️ Current Architecture

The current codebase establishes the Core/Spatial and Intelligence layers:

🎮 World Engine (Spatial Layer)

  • Rendering: React Three Fiber (R3F) & Three.js for high-performance WebGL graphics.
  • Physics & Environment:
    • Dynamic Time System (Day/Night cycles) with accurate Sun/Moon positioning.
    • Procedural Terrain generation using FBM noise & Instanced foliage.
    • Atmospheric Zone Controller for smooth Fog/Lighting transitions between biomes.
    • Collision detection with Raycasting and Height-field physics.

🤖 AI System (Intelligence Layer)

  • Brain: Integrated with Google Gemini 2.5 Flash for high-level decision making.
    • Perception: Agents "see" nearby entities (Players, Agents, Obstacles) and their status.
    • Reasoning: Agents autonomously decide to Follow, Wander, Chat, or Wait based on visual context.
  • Motor Control: Powered by Yuka AI for autonomous steering behaviors.
    • Seek, Wander, Separation, ObstacleAvoidance.
    • Smooth navigation and separation logic for crowd dynamics.
  • Social:
    • Agent-to-Agent interactions (Greeting, Chatting states).
    • Agent-to-Player interactions (Look-at, Waving, Following).

🛠 Tech Stack

  • Framework: Next.js 16 (React 19)
  • Language: TypeScript
  • State Management: Zustand
  • AI/ML: Google GenAI SDK (Gemini), Yuka GameAI
  • 3D: React Three Fiber, Drei

💻 Getting Started

Prerequisites

  • Node.js 18+
  • pnpm (recommended) or npm
  • Google Gemini API Key

Installation

  1. Clone the repository

    git clone https://github.com/Cortana-Devs/Descendants.git
    cd Descendants
  2. Install dependencies

    pnpm install
  3. Environment Setup Create a .env.local file in the root directory:

    NEXT_PUBLIC_GEMINI_API_KEY=your_api_key_here
  4. Run Development Server

    pnpm dev

    Open http://localhost:3000 to enter the simulation.


🗺️ Roadmap

Phase Status Feature
Phase 1: Foundation Core 3D Engine, Procedural Terrain, Day/Night Cycle
Phase 2: Intelligence Gemini 2.5 Integration, Yuka Steering, Basic Agent Behaviors
Phase 3: Social 🚧 Multi-Agent Chat, Group Dynamics, "Simulacra" Personality Engine
Phase 4: Expansion Infinite Terrain, MCP Integration, RealityLink Prototype
Phase 5: CortanaOS 🔮 Full Operating System Logic, Async Priority Queues, Deep Memory

🤝 Contributing

We welcome contributions from industry experts and engineers.

  1. Fork the repository.
  2. Create your feature branch (git checkout -b feature/amazing-feature).
  3. Commit your changes (git commit -m 'Add some amazing feature').
  4. Push to the branch (git push origin feature/amazing-feature).
  5. Open a Pull Request.

📄 License

Distributed under the MIT License. See LICENSE for more information.


Designed and engineered by the Cortana Research & Development Center.

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