Agentic System Architecture Layer

An Agentic System Architecture Layer is a AI system architecture layer in an layer-based AI-agent architecture model that organizes AI agent components (to support agent-based capabilitys through agent layer organization).

• AKA: Agent Architecture Layer, AI Agent Layer.
• Context:
  • It can (typically) organize Agent Components through layer hierarchys.
  • It can typically manage Agent Lifecycle through development layers.
  • It can typically handle Agent Logic through reasoning layers.
  • It can typically support Agent Interaction through communication layers.
  • It can typically coordinate Agent State through memory layers.
  • ...
  • It can often implement Agent Learning through adaptation layers.
  • It can often provide Tool Integration through interface layers.
  • It can often manage Agent Deployment through serving layers.
  • It can often support Agent Monitoring through observability layers.
  • ...
  • It can range from being a Simple Agent Layer to being a Complex Agent Layer, depending on its agent capability.
  • It can range from being a Specialized Agent Layer to being a General Agent Layer, depending on its agent scope.
  • It can range from being a Stateless Agent Layer to being a Stateful Agent Layer, depending on its memory requirement.
  • ...
  • It can integrate with Model Software Layer for AI models.
  • It can connect to Tool Software Layer for external tools.
  • It can utilize Knowledge Software Layer for information access.
  • ...
• Examples:
  • Agentic System Core Layers, such as:
    • Agentic System Planning Layers for strategy-based agents.
    • Agentic System Reasoning Layers for decision-based agents.
    • Agentic System Learning Layers for adaptive agents.
  • Agentic System Interaction Layers, such as:
    • Agentic System Tool Integration Layers for tool-using agents.
    • Agentic System API Connection Layers for service-based agents.
    • Agentic System Environment Interface Layers for environment-aware agents.
  • Agentic System Memory Layers, such as:
    • Agentic System Context Management Layers for context-aware agents.
    • Agentic System Knowledge Base Layers for knowledge-driven agents.
    • Agentic System State Tracking Layers for stateful agents.
  • ...
• Counter-Examples:
  • Traditional Software Layer, which lacks agent-specific capabilitys.
  • AI Model Layer, which focuses on model execution rather than agent behavior.
  • Service Layer, which handles request processing rather than autonomous action.
• See: AI Agent Architecture, Agent System Design, AI Layer Pattern, Agent Development Lifecycle.

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