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Blade Games
  • Blade Games Whitepaper
    • Blade Games
  • BLADE GAMES OVERVIEW
    • Who We Are
    • Key Partnerships
    • Our Team
  • Dune Factory
    • Gameplay, Play-and-Mine
      • Dune Factory Gameplay Guide
      • Play-and-Mine (Please Wait For New Season)
      • Resources
      • Monster Compendium
    • Private Test (Finished)
      • Must-knows
      • Invite Codes
    • Dune Factory Public Test
  • AI Agents in Blade Games
    • Blade Games AI Agent Overview
    • Our Design Framework
    • How AI Agents Drive Revenue in the Ecosystem
    • Blade Games AI Agent Use Cases
    • Blade Games AI Agent Plan
    • Games Ecosystem That You Can Play
  • ZKUNITY - GAME ENGINE
    • ZKUnity Guide
      • zkWASM
      • ZKUnity
      • Architecture
      • MVC Programming Pattern
      • Demo - a roguelike card game
        • Prerequisites
        • How to run
        • How to play
        • Dir Structure
        • Guide for the backend code
        • Guide for the frontend code
        • ZK Proof
  • Tokenomics
    • Token Utility
    • Token Distribution/Allocation
    • Treasury Wallets Disclosure
  • Important
    • Roadmap
    • Feedback
    • Investors
    • Official Links
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  1. AI Agents in Blade Games

Our Design Framework

  1. AGENT INITIALIZATION ARCHITECTURE

A. Character Consciousness Layer

  • Initialize unique personality profiles through the Agent Prompting Interface

  • Create a persistent memory footprint via Long Term Memory Processor

B. Building Behavioral Foundation

  • Define core character motivations and goals

  • Establish relationship parameters with other NPCs/players

  • Set initial knowledge boundaries and learning parameters

  1. PERCEPTION AND RESPONSE SYSTEM

A. Environmental Understanding

  • Perception Subsystem processes real-time game world data

  • Analyzes player movements, actions, and environmental changes

  • Creates contextual awareness for decision-making

B. Strategic Response Generation

  • Strategic Planning Engine evaluates multiple action possibilities

  • Weighs decisions against character personality and past experiences

  • Generates appropriate responses based on current context and memory

  1. MEMORY AND LEARNING FRAMEWORK

A. Knowledge Evolution

  • Develops new behavior patterns based on successful interactions

  • Updates character personality based on significant events

  • Refines decision-making through accumulated experiences

  1. INTERACTION DYNAMICS

A. Player Engagement

  • Dialogue Processing Module handles natural conversations

  • Adapts communication style based on relationship history

  • Maintains conversation coherence through memory context

  1. SCALING CONSIDERATIONS

A. Multi-Agent Management

  • Coordinates multiple AI agents efficiently

  • Manages resource allocation across agent networks

  • Handles concurrent agent interactions

B. World Integration

  • Syncs agent behaviors with the game world state

  • Maintain consistent character development

  • Scales system based on world complexity

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Last updated 4 months ago