📖Agent: Next Generation App

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Agent Working Principle

Agent structure is decomposed into four main components: Environment, Perception, Brain, and Action. These components together form a complete feedback loop, enabling intelligent agents to interact with the environment and achieve goals.
  1. Environment Environment is the external world where agents exist. Through Agent Prompting Interface as gateway, agents perceive and receive various information from environment. This includes user commands, physical scenes, and behaviors of other entities.
  1. Perception The perception subsystem processes and synthesizes multimodal inputs from the environment, including text, images, audio, etc. It converts these raw data into vector representations for use by subsequent strategy planning engine. The perception system design ensures agents can accurately understand environmental states and user intentions.
  1. Brain The brain module is the core decision-making center of agents, consisting of the following key parts:
      • Long-term Memory Processor
        • Efficiently extract relevant experiences and reflections
        • Dynamically adjust personality traits
        • Maintain world knowledge context
        • Manage working memory
      • Strategy Planning Engine
        • Work with dialogue processing module
        • Call on-chain wallet operation module
        • Formulate action plans and decisions
        • Evaluate action results and feedback
      • Knowledge Storage System
        • Memory bank: store short-term interaction information
        • Knowledge base: accumulate long-term system knowledge
        • Continuous learning: constantly optimize decision-making ability
  1. Action The action module is responsible for executing agent decisions, mainly including:
      • Text Output: Generate dialogue responses
      • Tool Calling: Access external APIs and services
      • Physical Interaction: Control robots and other physical devices
The overall architecture achieves continuous optimization through complete feedback loop:
  • Perceive environmental input
  • Analyze and understand information
  • Plan and decide actions
  • Execute and evaluate
  • Update knowledge base
  • Optimize future decisions
This modular design allows developers to easily integrate and use agents in projects, achieving plug-and-play. The system supports multimodal interaction, can handle complex tasks, and improves performance through continuous learning.
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Agents Reshape the World

DeepAI continuously explores possible AI technology applications, building rich and diverse functional ecosystem:
⭐️ Immersive Gaming
  • Dynamic plot generation based on large language models
  • Personalized NPC behavior system, providing real interactive experience
  • Real-time game scene adaptation, adjusting difficulty based on player behavior
  • Multiplayer game intelligent scheduling, optimizing gaming experience
⭐️ Intelligent Finance
  • Multi-source data real-time analysis, including on-chain data, market information and social signals
  • Risk assessment model based on machine learning, accurately predicting market trends
  • Automated trading strategy execution, supporting multi-chain multi-currency
  • Real-time risk control system, intelligent stop loss and profit optimization
⭐️ Cultural Creation
  • Multimodal content generation, supporting text, audio, video and other formats
  • AI-driven podcast production, including topic selection, scripting and audio processing
  • Virtual host personalization customization, supporting real-time expression and action generation
  • Digital art creation assistance, providing professional creative suggestions
⭐️ Blockchain Economy
  • Smart contract automatic generation and audit, ensuring code security
  • Token economic model design and optimization
  • Cross-chain data analysis, providing market insights
  • Decentralized identity authentication, protecting user privacy
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