Agentora White Paper
  • Preface
  • 1. Agentora
  • 2. Key Technologies
    • 2.1 Federated Learning Framework and AI Agents
    • 2.2 ZKML Verification Protocol
    • 2.3 Dynamic Game Engine
    • 2.4 Triple Trust Verification System
    • 2.5 Tokenized Computational Power Market and AI Training Tax Mechanism
  • 3. Web3 AI Economy
    • 3.1 Autonomous Universe of GameFi
    • 3.2 AI Agent Native Driver
    • 3.3 Self-earning Capability
  • 4. Tokenomics
    • 4.1 $ATA (Agentora Token)
    • 4.2 ATA Application and Circulation
  • 5. Roadmap
  • 6. Investment and Project Risk Information
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  1. 3. Web3 AI Economy

3.2 AI Agent Native Driver

  • Intelligent Asset Management： At the core of Agentora is the native drive of AI Agents. Each player is equipped with a dedicated Neuro Agent. These intelligent agents, relying on federated learning for continuous evolution, automatically manage assets, optimize trading strategies, and swiftly respond to market changes, providing players with customized operational advice.

  • Self-evolving Mechanism: AI Agents continuously learn from player behavior and market data to enhance their decision-making capabilities. Leveraging the synergy of reinforcement learning and federated learning, Neuro Agents can achieve globally optimal strategy adjustments while protecting privacy, maintaining a competitive edge in the complex and dynamic GameFi ecosystem.

  • Cross-chain Coordination and Data Interoperability: AI Agents integrate cross-chain data deeply to coordinate asset flows across multiple blockchain environments, offering players a panoramic market analysis. Whether on Ethereum, Solana, or other blockchains, AI Agents manage assets and execute strategies to a unified standard, truly realizing intelligent, seamless cross-chain coordination.

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Last updated 3 months ago