Kodeus.ai
  • Abstract
  • Introduction
  • K-MAF - Core Architecture
    • Agent Creation
    • LifeWeaver – The Fostering & Nurturing Framework
    • Training and Specialization – InfinityEvolve
      • SkillCrafter: Interactive Training Modules
      • Augmentix: Agent Ability Augmentation
      • MetaMind: The Adaptive Learning Framework
    • Multi-Agent Interaction Design – NeuroNexus
    • Security, Resilience and Loyalty - NeuroGuard
      • State Management and Recovery
      • Data Integrity and Compliance
      • Loyalty and Trust Mechanisms
  • Performance Optimization
    • Memory Optimization: Smarter Data Management
    • Energy Efficiency: Doing More with Less
    • Dynamic Resource Allocation: Smart and Flexible
    • Learning Optimization: Faster and Smarter Training
    • Scalability and Future-Proofing
  • Plugins and Integrations
  • Agentic Kodeus Protocol on Blockchain
    • NFT-Based Agent Representation (ERC721)
    • Token Bound Accounts (ERC4337) for Autonomous Operations
    • Agent Lifecycle and Ownership Transfer
    • Tokenized Economy and Agent-Specific Tokens
    • Leasing and Delegation Capabilities
    • Security and Compliance
  • The Kodeus Edge
    • Deployment in a Containerized Environment
    • System-Level Interactions
    • Advanced Automation and Decision-Making
    • Scalability and Portability
    • Enhanced Programming and Customization Capabilities
    • Gene-Based Agent Creation
    • Hierarchical Reinforcement Learning (HRL)
    • Decentralized Knowledge Base (DKB)
    • Integration Capabilities
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  1. K-MAF - Core Architecture
  2. Training and Specialization – InfinityEvolve

Augmentix: Agent Ability Augmentation

Augmentix empowers developers and businesses to expand an agent’s capabilities by integrating custom functionalities through extendable frameworks, ensuring adaptability and scalability. Training begins with access to the Decentralized Knowledge Base (DKB), a shared repository of insights and data. Agents don’t start from scratch—they learn from the experiences and insights contributed by others before them. The Key Attributes are;

  • Wrappers to seamlessly integrate with existing frameworks and AI tools.

  • Modular architecture to enable flexible enhancements and new skill additions.

  • Plug-and-play APIs for integrating specialized domain expertise.

  • AI performance monitoring and analytics to optimize enhanced capabilities.

  • Secure environment ensuring data privacy and compliance with regulatory standards.

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Last updated 3 months ago